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Xtra-Computing / ThundersvmThunderSVM: A Fast SVM Library on GPUs and CPUs
lukasruff / Deep SVDD PyTorchA PyTorch implementation of the Deep SVDD anomaly detection method
lukasruff / Deep SAD PyTorchA PyTorch implementation of Deep SAD, a deep Semi-supervised Anomaly Detection method.
SartHak-0-Sach / Harkirat Singh Course Code And NotesA comprehensive resource hub for mastering web development, covering everything from fundamental concepts to advanced topics and project-based learning. This also includes my notes on various other bonus sections offered alongside the course such as the MLops section, native android development section and DSA classes all in one. Follow for more😁✨
sayantann11 / All Classification Templetes For MLClassification - Machine Learning This is ‘Classification’ tutorial which is a part of the Machine Learning course offered by Simplilearn. We will learn Classification algorithms, types of classification algorithms, support vector machines(SVM), Naive Bayes, Decision Tree and Random Forest Classifier in this tutorial. Objectives Let us look at some of the objectives covered under this section of Machine Learning tutorial. Define Classification and list its algorithms Describe Logistic Regression and Sigmoid Probability Explain K-Nearest Neighbors and KNN classification Understand Support Vector Machines, Polynomial Kernel, and Kernel Trick Analyze Kernel Support Vector Machines with an example Implement the Naïve Bayes Classifier Demonstrate Decision Tree Classifier Describe Random Forest Classifier Classification: Meaning Classification is a type of supervised learning. It specifies the class to which data elements belong to and is best used when the output has finite and discrete values. It predicts a class for an input variable as well. There are 2 types of Classification: Binomial Multi-Class Classification: Use Cases Some of the key areas where classification cases are being used: To find whether an email received is a spam or ham To identify customer segments To find if a bank loan is granted To identify if a kid will pass or fail in an examination Classification: Example Social media sentiment analysis has two potential outcomes, positive or negative, as displayed by the chart given below. https://www.simplilearn.com/ice9/free_resources_article_thumb/classification-example-machine-learning.JPG This chart shows the classification of the Iris flower dataset into its three sub-species indicated by codes 0, 1, and 2. https://www.simplilearn.com/ice9/free_resources_article_thumb/iris-flower-dataset-graph.JPG The test set dots represent the assignment of new test data points to one class or the other based on the trained classifier model. Types of Classification Algorithms Let’s have a quick look into the types of Classification Algorithm below. Linear Models Logistic Regression Support Vector Machines Nonlinear models K-nearest Neighbors (KNN) Kernel Support Vector Machines (SVM) Naïve Bayes Decision Tree Classification Random Forest Classification Logistic Regression: Meaning Let us understand the Logistic Regression model below. This refers to a regression model that is used for classification. This method is widely used for binary classification problems. It can also be extended to multi-class classification problems. Here, the dependent variable is categorical: y ϵ {0, 1} A binary dependent variable can have only two values, like 0 or 1, win or lose, pass or fail, healthy or sick, etc In this case, you model the probability distribution of output y as 1 or 0. This is called the sigmoid probability (σ). If σ(θ Tx) > 0.5, set y = 1, else set y = 0 Unlike Linear Regression (and its Normal Equation solution), there is no closed form solution for finding optimal weights of Logistic Regression. Instead, you must solve this with maximum likelihood estimation (a probability model to detect the maximum likelihood of something happening). It can be used to calculate the probability of a given outcome in a binary model, like the probability of being classified as sick or passing an exam. https://www.simplilearn.com/ice9/free_resources_article_thumb/logistic-regression-example-graph.JPG Sigmoid Probability The probability in the logistic regression is often represented by the Sigmoid function (also called the logistic function or the S-curve): https://www.simplilearn.com/ice9/free_resources_article_thumb/sigmoid-function-machine-learning.JPG In this equation, t represents data values * the number of hours studied and S(t) represents the probability of passing the exam. Assume sigmoid function: https://www.simplilearn.com/ice9/free_resources_article_thumb/sigmoid-probability-machine-learning.JPG g(z) tends toward 1 as z -> infinity , and g(z) tends toward 0 as z -> infinity K-nearest Neighbors (KNN) K-nearest Neighbors algorithm is used to assign a data point to clusters based on similarity measurement. It uses a supervised method for classification. The steps to writing a k-means algorithm are as given below: https://www.simplilearn.com/ice9/free_resources_article_thumb/knn-distribution-graph-machine-learning.JPG Choose the number of k and a distance metric. (k = 5 is common) Find k-nearest neighbors of the sample that you want to classify Assign the class label by majority vote. KNN Classification A new input point is classified in the category such that it has the most number of neighbors from that category. For example: https://www.simplilearn.com/ice9/free_resources_article_thumb/knn-classification-machine-learning.JPG Classify a patient as high risk or low risk. Mark email as spam or ham. Keen on learning about Classification Algorithms in Machine Learning? Click here! Support Vector Machine (SVM) Let us understand Support Vector Machine (SVM) in detail below. SVMs are classification algorithms used to assign data to various classes. They involve detecting hyperplanes which segregate data into classes. SVMs are very versatile and are also capable of performing linear or nonlinear classification, regression, and outlier detection. Once ideal hyperplanes are discovered, new data points can be easily classified. https://www.simplilearn.com/ice9/free_resources_article_thumb/support-vector-machines-graph-machine-learning.JPG The optimization objective is to find “maximum margin hyperplane” that is farthest from the closest points in the two classes (these points are called support vectors). In the given figure, the middle line represents the hyperplane. SVM Example Let’s look at this image below and have an idea about SVM in general. Hyperplanes with larger margins have lower generalization error. The positive and negative hyperplanes are represented by: https://www.simplilearn.com/ice9/free_resources_article_thumb/positive-negative-hyperplanes-machine-learning.JPG Classification of any new input sample xtest : If w0 + wTxtest > 1, the sample xtest is said to be in the class toward the right of the positive hyperplane. If w0 + wTxtest < -1, the sample xtest is said to be in the class toward the left of the negative hyperplane. When you subtract the two equations, you get: https://www.simplilearn.com/ice9/free_resources_article_thumb/equation-subtraction-machine-learning.JPG Length of vector w is (L2 norm length): https://www.simplilearn.com/ice9/free_resources_article_thumb/length-of-vector-machine-learning.JPG You normalize with the length of w to arrive at: https://www.simplilearn.com/ice9/free_resources_article_thumb/normalize-equation-machine-learning.JPG SVM: Hard Margin Classification Given below are some points to understand Hard Margin Classification. The left side of equation SVM-1 given above can be interpreted as the distance between the positive (+ve) and negative (-ve) hyperplanes; in other words, it is the margin that can be maximized. Hence the objective of the function is to maximize with the constraint that the samples are classified correctly, which is represented as : https://www.simplilearn.com/ice9/free_resources_article_thumb/hard-margin-classification-machine-learning.JPG This means that you are minimizing ‖w‖. This also means that all positive samples are on one side of the positive hyperplane and all negative samples are on the other side of the negative hyperplane. This can be written concisely as : https://www.simplilearn.com/ice9/free_resources_article_thumb/hard-margin-classification-formula.JPG Minimizing ‖w‖ is the same as minimizing. This figure is better as it is differentiable even at w = 0. The approach listed above is called “hard margin linear SVM classifier.” SVM: Soft Margin Classification Given below are some points to understand Soft Margin Classification. To allow for linear constraints to be relaxed for nonlinearly separable data, a slack variable is introduced. (i) measures how much ith instance is allowed to violate the margin. The slack variable is simply added to the linear constraints. https://www.simplilearn.com/ice9/free_resources_article_thumb/soft-margin-calculation-machine-learning.JPG Subject to the above constraints, the new objective to be minimized becomes: https://www.simplilearn.com/ice9/free_resources_article_thumb/soft-margin-calculation-formula.JPG You have two conflicting objectives now—minimizing slack variable to reduce margin violations and minimizing to increase the margin. The hyperparameter C allows us to define this trade-off. Large values of C correspond to larger error penalties (so smaller margins), whereas smaller values of C allow for higher misclassification errors and larger margins. https://www.simplilearn.com/ice9/free_resources_article_thumb/machine-learning-certification-video-preview.jpg SVM: Regularization The concept of C is the reverse of regularization. Higher C means lower regularization, which increases bias and lowers the variance (causing overfitting). https://www.simplilearn.com/ice9/free_resources_article_thumb/concept-of-c-graph-machine-learning.JPG IRIS Data Set The Iris dataset contains measurements of 150 IRIS flowers from three different species: Setosa Versicolor Viriginica Each row represents one sample. Flower measurements in centimeters are stored as columns. These are called features. IRIS Data Set: SVM Let’s train an SVM model using sci-kit-learn for the Iris dataset: https://www.simplilearn.com/ice9/free_resources_article_thumb/svm-model-graph-machine-learning.JPG Nonlinear SVM Classification There are two ways to solve nonlinear SVMs: by adding polynomial features by adding similarity features Polynomial features can be added to datasets; in some cases, this can create a linearly separable dataset. https://www.simplilearn.com/ice9/free_resources_article_thumb/nonlinear-classification-svm-machine-learning.JPG In the figure on the left, there is only 1 feature x1. This dataset is not linearly separable. If you add x2 = (x1)2 (figure on the right), the data becomes linearly separable. Polynomial Kernel In sci-kit-learn, one can use a Pipeline class for creating polynomial features. Classification results for the Moons dataset are shown in the figure. https://www.simplilearn.com/ice9/free_resources_article_thumb/polynomial-kernel-machine-learning.JPG Polynomial Kernel with Kernel Trick Let us look at the image below and understand Kernel Trick in detail. https://www.simplilearn.com/ice9/free_resources_article_thumb/polynomial-kernel-with-kernel-trick.JPG For large dimensional datasets, adding too many polynomial features can slow down the model. You can apply a kernel trick with the effect of polynomial features without actually adding them. The code is shown (SVC class) below trains an SVM classifier using a 3rd-degree polynomial kernel but with a kernel trick. https://www.simplilearn.com/ice9/free_resources_article_thumb/polynomial-kernel-equation-machine-learning.JPG The hyperparameter coefθ controls the influence of high-degree polynomials. Kernel SVM Let us understand in detail about Kernel SVM. Kernel SVMs are used for classification of nonlinear data. In the chart, nonlinear data is projected into a higher dimensional space via a mapping function where it becomes linearly separable. https://www.simplilearn.com/ice9/free_resources_article_thumb/kernel-svm-machine-learning.JPG In the higher dimension, a linear separating hyperplane can be derived and used for classification. A reverse projection of the higher dimension back to original feature space takes it back to nonlinear shape. As mentioned previously, SVMs can be kernelized to solve nonlinear classification problems. You can create a sample dataset for XOR gate (nonlinear problem) from NumPy. 100 samples will be assigned the class sample 1, and 100 samples will be assigned the class label -1. https://www.simplilearn.com/ice9/free_resources_article_thumb/kernel-svm-graph-machine-learning.JPG As you can see, this data is not linearly separable. https://www.simplilearn.com/ice9/free_resources_article_thumb/kernel-svm-non-separable.JPG You now use the kernel trick to classify XOR dataset created earlier. https://www.simplilearn.com/ice9/free_resources_article_thumb/kernel-svm-xor-machine-learning.JPG Naïve Bayes Classifier What is Naive Bayes Classifier? Have you ever wondered how your mail provider implements spam filtering or how online news channels perform news text classification or even how companies perform sentiment analysis of their audience on social media? All of this and more are done through a machine learning algorithm called Naive Bayes Classifier. Naive Bayes Named after Thomas Bayes from the 1700s who first coined this in the Western literature. Naive Bayes classifier works on the principle of conditional probability as given by the Bayes theorem. Advantages of Naive Bayes Classifier Listed below are six benefits of Naive Bayes Classifier. Very simple and easy to implement Needs less training data Handles both continuous and discrete data Highly scalable with the number of predictors and data points As it is fast, it can be used in real-time predictions Not sensitive to irrelevant features Bayes Theorem We will understand Bayes Theorem in detail from the points mentioned below. According to the Bayes model, the conditional probability P(Y|X) can be calculated as: P(Y|X) = P(X|Y)P(Y) / P(X) This means you have to estimate a very large number of P(X|Y) probabilities for a relatively small vector space X. For example, for a Boolean Y and 30 possible Boolean attributes in the X vector, you will have to estimate 3 billion probabilities P(X|Y). To make it practical, a Naïve Bayes classifier is used, which assumes conditional independence of P(X) to each other, with a given value of Y. This reduces the number of probability estimates to 2*30=60 in the above example. Naïve Bayes Classifier for SMS Spam Detection Consider a labeled SMS database having 5574 messages. It has messages as given below: https://www.simplilearn.com/ice9/free_resources_article_thumb/naive-bayes-spam-machine-learning.JPG Each message is marked as spam or ham in the data set. Let’s train a model with Naïve Bayes algorithm to detect spam from ham. The message lengths and their frequency (in the training dataset) are as shown below: https://www.simplilearn.com/ice9/free_resources_article_thumb/naive-bayes-spam-spam-detection.JPG Analyze the logic you use to train an algorithm to detect spam: Split each message into individual words/tokens (bag of words). Lemmatize the data (each word takes its base form, like “walking” or “walked” is replaced with “walk”). Convert data to vectors using scikit-learn module CountVectorizer. Run TFIDF to remove common words like “is,” “are,” “and.” Now apply scikit-learn module for Naïve Bayes MultinomialNB to get the Spam Detector. This spam detector can then be used to classify a random new message as spam or ham. Next, the accuracy of the spam detector is checked using the Confusion Matrix. For the SMS spam example above, the confusion matrix is shown on the right. Accuracy Rate = Correct / Total = (4827 + 592)/5574 = 97.21% Error Rate = Wrong / Total = (155 + 0)/5574 = 2.78% https://www.simplilearn.com/ice9/free_resources_article_thumb/confusion-matrix-machine-learning.JPG Although confusion Matrix is useful, some more precise metrics are provided by Precision and Recall. https://www.simplilearn.com/ice9/free_resources_article_thumb/precision-recall-matrix-machine-learning.JPG Precision refers to the accuracy of positive predictions. https://www.simplilearn.com/ice9/free_resources_article_thumb/precision-formula-machine-learning.JPG Recall refers to the ratio of positive instances that are correctly detected by the classifier (also known as True positive rate or TPR). https://www.simplilearn.com/ice9/free_resources_article_thumb/recall-formula-machine-learning.JPG Precision/Recall Trade-off To detect age-appropriate videos for kids, you need high precision (low recall) to ensure that only safe videos make the cut (even though a few safe videos may be left out). The high recall is needed (low precision is acceptable) in-store surveillance to catch shoplifters; a few false alarms are acceptable, but all shoplifters must be caught. Learn about Naive Bayes in detail. Click here! Decision Tree Classifier Some aspects of the Decision Tree Classifier mentioned below are. Decision Trees (DT) can be used both for classification and regression. The advantage of decision trees is that they require very little data preparation. They do not require feature scaling or centering at all. They are also the fundamental components of Random Forests, one of the most powerful ML algorithms. Unlike Random Forests and Neural Networks (which do black-box modeling), Decision Trees are white box models, which means that inner workings of these models are clearly understood. In the case of classification, the data is segregated based on a series of questions. Any new data point is assigned to the selected leaf node. https://www.simplilearn.com/ice9/free_resources_article_thumb/decision-tree-classifier-machine-learning.JPG Start at the tree root and split the data on the feature using the decision algorithm, resulting in the largest information gain (IG). This splitting procedure is then repeated in an iterative process at each child node until the leaves are pure. This means that the samples at each node belonging to the same class. In practice, you can set a limit on the depth of the tree to prevent overfitting. The purity is compromised here as the final leaves may still have some impurity. The figure shows the classification of the Iris dataset. https://www.simplilearn.com/ice9/free_resources_article_thumb/decision-tree-classifier-graph.JPG IRIS Decision Tree Let’s build a Decision Tree using scikit-learn for the Iris flower dataset and also visualize it using export_graphviz API. https://www.simplilearn.com/ice9/free_resources_article_thumb/iris-decision-tree-machine-learning.JPG The output of export_graphviz can be converted into png format: https://www.simplilearn.com/ice9/free_resources_article_thumb/iris-decision-tree-output.JPG Sample attribute stands for the number of training instances the node applies to. Value attribute stands for the number of training instances of each class the node applies to. Gini impurity measures the node’s impurity. A node is “pure” (gini=0) if all training instances it applies to belong to the same class. https://www.simplilearn.com/ice9/free_resources_article_thumb/impurity-formula-machine-learning.JPG For example, for Versicolor (green color node), the Gini is 1-(0/54)2 -(49/54)2 -(5/54) 2 ≈ 0.168 https://www.simplilearn.com/ice9/free_resources_article_thumb/iris-decision-tree-sample.JPG Decision Boundaries Let us learn to create decision boundaries below. For the first node (depth 0), the solid line splits the data (Iris-Setosa on left). Gini is 0 for Setosa node, so no further split is possible. The second node (depth 1) splits the data into Versicolor and Virginica. If max_depth were set as 3, a third split would happen (vertical dotted line). https://www.simplilearn.com/ice9/free_resources_article_thumb/decision-tree-boundaries.JPG For a sample with petal length 5 cm and petal width 1.5 cm, the tree traverses to depth 2 left node, so the probability predictions for this sample are 0% for Iris-Setosa (0/54), 90.7% for Iris-Versicolor (49/54), and 9.3% for Iris-Virginica (5/54) CART Training Algorithm Scikit-learn uses Classification and Regression Trees (CART) algorithm to train Decision Trees. CART algorithm: Split the data into two subsets using a single feature k and threshold tk (example, petal length < “2.45 cm”). This is done recursively for each node. k and tk are chosen such that they produce the purest subsets (weighted by their size). The objective is to minimize the cost function as given below: https://www.simplilearn.com/ice9/free_resources_article_thumb/cart-training-algorithm-machine-learning.JPG The algorithm stops executing if one of the following situations occurs: max_depth is reached No further splits are found for each node Other hyperparameters may be used to stop the tree: min_samples_split min_samples_leaf min_weight_fraction_leaf max_leaf_nodes Gini Impurity or Entropy Entropy is one more measure of impurity and can be used in place of Gini. https://www.simplilearn.com/ice9/free_resources_article_thumb/gini-impurity-entrophy.JPG It is a degree of uncertainty, and Information Gain is the reduction that occurs in entropy as one traverses down the tree. Entropy is zero for a DT node when the node contains instances of only one class. Entropy for depth 2 left node in the example given above is: https://www.simplilearn.com/ice9/free_resources_article_thumb/entrophy-for-depth-2.JPG Gini and Entropy both lead to similar trees. DT: Regularization The following figure shows two decision trees on the moons dataset. https://www.simplilearn.com/ice9/free_resources_article_thumb/dt-regularization-machine-learning.JPG The decision tree on the right is restricted by min_samples_leaf = 4. The model on the left is overfitting, while the model on the right generalizes better. Random Forest Classifier Let us have an understanding of Random Forest Classifier below. A random forest can be considered an ensemble of decision trees (Ensemble learning). Random Forest algorithm: Draw a random bootstrap sample of size n (randomly choose n samples from the training set). Grow a decision tree from the bootstrap sample. At each node, randomly select d features. Split the node using the feature that provides the best split according to the objective function, for instance by maximizing the information gain. Repeat the steps 1 to 2 k times. (k is the number of trees you want to create, using a subset of samples) Aggregate the prediction by each tree for a new data point to assign the class label by majority vote (pick the group selected by the most number of trees and assign new data point to that group). Random Forests are opaque, which means it is difficult to visualize their inner workings. https://www.simplilearn.com/ice9/free_resources_article_thumb/random-forest-classifier-graph.JPG However, the advantages outweigh their limitations since you do not have to worry about hyperparameters except k, which stands for the number of decision trees to be created from a subset of samples. RF is quite robust to noise from the individual decision trees. Hence, you need not prune individual decision trees. The larger the number of decision trees, the more accurate the Random Forest prediction is. (This, however, comes with higher computation cost). Key Takeaways Let us quickly run through what we have learned so far in this Classification tutorial. Classification algorithms are supervised learning methods to split data into classes. They can work on Linear Data as well as Nonlinear Data. Logistic Regression can classify data based on weighted parameters and sigmoid conversion to calculate the probability of classes. K-nearest Neighbors (KNN) algorithm uses similar features to classify data. Support Vector Machines (SVMs) classify data by detecting the maximum margin hyperplane between data classes. Naïve Bayes, a simplified Bayes Model, can help classify data using conditional probability models. Decision Trees are powerful classifiers and use tree splitting logic until pure or somewhat pure leaf node classes are attained. Random Forests apply Ensemble Learning to Decision Trees for more accurate classification predictions. Conclusion This completes ‘Classification’ tutorial. In the next tutorial, we will learn 'Unsupervised Learning with Clustering.'
molyswu / Hand Detectionusing Neural Networks (SSD) on Tensorflow. This repo documents steps and scripts used to train a hand detector using Tensorflow (Object Detection API). As with any DNN based task, the most expensive (and riskiest) part of the process has to do with finding or creating the right (annotated) dataset. I was interested mainly in detecting hands on a table (egocentric view point). I experimented first with the [Oxford Hands Dataset](http://www.robots.ox.ac.uk/~vgg/data/hands/) (the results were not good). I then tried the [Egohands Dataset](http://vision.soic.indiana.edu/projects/egohands/) which was a much better fit to my requirements. The goal of this repo/post is to demonstrate how neural networks can be applied to the (hard) problem of tracking hands (egocentric and other views). Better still, provide code that can be adapted to other uses cases. If you use this tutorial or models in your research or project, please cite [this](#citing-this-tutorial). Here is the detector in action. <img src="images/hand1.gif" width="33.3%"><img src="images/hand2.gif" width="33.3%"><img src="images/hand3.gif" width="33.3%"> Realtime detection on video stream from a webcam . <img src="images/chess1.gif" width="33.3%"><img src="images/chess2.gif" width="33.3%"><img src="images/chess3.gif" width="33.3%"> Detection on a Youtube video. Both examples above were run on a macbook pro **CPU** (i7, 2.5GHz, 16GB). Some fps numbers are: | FPS | Image Size | Device| Comments| | ------------- | ------------- | ------------- | ------------- | | 21 | 320 * 240 | Macbook pro (i7, 2.5GHz, 16GB) | Run without visualizing results| | 16 | 320 * 240 | Macbook pro (i7, 2.5GHz, 16GB) | Run while visualizing results (image above) | | 11 | 640 * 480 | Macbook pro (i7, 2.5GHz, 16GB) | Run while visualizing results (image above) | > Note: The code in this repo is written and tested with Tensorflow `1.4.0-rc0`. Using a different version may result in [some errors](https://github.com/tensorflow/models/issues/1581). You may need to [generate your own frozen model](https://pythonprogramming.net/testing-custom-object-detector-tensorflow-object-detection-api-tutorial/?completed=/training-custom-objects-tensorflow-object-detection-api-tutorial/) graph using the [model checkpoints](model-checkpoint) in the repo to fit your TF version. **Content of this document** - Motivation - Why Track/Detect hands with Neural Networks - Data preparation and network training in Tensorflow (Dataset, Import, Training) - Training the hand detection Model - Using the Detector to Detect/Track hands - Thoughts on Optimizations. > P.S if you are using or have used the models provided here, feel free to reach out on twitter ([@vykthur](https://twitter.com/vykthur)) and share your work! ## Motivation - Why Track/Detect hands with Neural Networks? There are several existing approaches to tracking hands in the computer vision domain. Incidentally, many of these approaches are rule based (e.g extracting background based on texture and boundary features, distinguishing between hands and background using color histograms and HOG classifiers,) making them not very robust. For example, these algorithms might get confused if the background is unusual or in situations where sharp changes in lighting conditions cause sharp changes in skin color or the tracked object becomes occluded.(see [here for a review](https://www.cse.unr.edu/~bebis/handposerev.pdf) paper on hand pose estimation from the HCI perspective) With sufficiently large datasets, neural networks provide opportunity to train models that perform well and address challenges of existing object tracking/detection algorithms - varied/poor lighting, noisy environments, diverse viewpoints and even occlusion. The main drawbacks to usage for real-time tracking/detection is that they can be complex, are relatively slow compared to tracking-only algorithms and it can be quite expensive to assemble a good dataset. But things are changing with advances in fast neural networks. Furthermore, this entire area of work has been made more approachable by deep learning frameworks (such as the tensorflow object detection api) that simplify the process of training a model for custom object detection. More importantly, the advent of fast neural network models like ssd, faster r-cnn, rfcn (see [here](https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md#coco-trained-models-coco-models) ) etc make neural networks an attractive candidate for real-time detection (and tracking) applications. Hopefully, this repo demonstrates this. > If you are not interested in the process of training the detector, you can skip straight to applying the [pretrained model I provide in detecting hands](#detecting-hands). Training a model is a multi-stage process (assembling dataset, cleaning, splitting into training/test partitions and generating an inference graph). While I lightly touch on the details of these parts, there are a few other tutorials cover training a custom object detector using the tensorflow object detection api in more detail[ see [here](https://pythonprogramming.net/training-custom-objects-tensorflow-object-detection-api-tutorial/) and [here](https://towardsdatascience.com/how-to-train-your-own-object-detector-with-tensorflows-object-detector-api-bec72ecfe1d9) ]. I recommend you walk through those if interested in training a custom object detector from scratch. ## Data preparation and network training in Tensorflow (Dataset, Import, Training) **The Egohands Dataset** The hand detector model is built using data from the [Egohands Dataset](http://vision.soic.indiana.edu/projects/egohands/) dataset. This dataset works well for several reasons. It contains high quality, pixel level annotations (>15000 ground truth labels) where hands are located across 4800 images. All images are captured from an egocentric view (Google glass) across 48 different environments (indoor, outdoor) and activities (playing cards, chess, jenga, solving puzzles etc). <img src="images/egohandstrain.jpg" width="100%"> If you will be using the Egohands dataset, you can cite them as follows: > Bambach, Sven, et al. "Lending a hand: Detecting hands and recognizing activities in complex egocentric interactions." Proceedings of the IEEE International Conference on Computer Vision. 2015. The Egohands dataset (zip file with labelled data) contains 48 folders of locations where video data was collected (100 images per folder). ``` -- LOCATION_X -- frame_1.jpg -- frame_2.jpg ... -- frame_100.jpg -- polygons.mat // contains annotations for all 100 images in current folder -- LOCATION_Y -- frame_1.jpg -- frame_2.jpg ... -- frame_100.jpg -- polygons.mat // contains annotations for all 100 images in current folder ``` **Converting data to Tensorflow Format** Some initial work needs to be done to the Egohands dataset to transform it into the format (`tfrecord`) which Tensorflow needs to train a model. This repo contains `egohands_dataset_clean.py` a script that will help you generate these csv files. - Downloads the egohands datasets - Renames all files to include their directory names to ensure each filename is unique - Splits the dataset into train (80%), test (10%) and eval (10%) folders. - Reads in `polygons.mat` for each folder, generates bounding boxes and visualizes them to ensure correctness (see image above). - Once the script is done running, you should have an images folder containing three folders - train, test and eval. Each of these folders should also contain a csv label document each - `train_labels.csv`, `test_labels.csv` that can be used to generate `tfrecords` Note: While the egohands dataset provides four separate labels for hands (own left, own right, other left, and other right), for my purpose, I am only interested in the general `hand` class and label all training data as `hand`. You can modify the data prep script to generate `tfrecords` that support 4 labels. Next: convert your dataset + csv files to tfrecords. A helpful guide on this can be found [here](https://pythonprogramming.net/creating-tfrecord-files-tensorflow-object-detection-api-tutorial/).For each folder, you should be able to generate `train.record`, `test.record` required in the training process. ## Training the hand detection Model Now that the dataset has been assembled (and your tfrecords), the next task is to train a model based on this. With neural networks, it is possible to use a process called [transfer learning](https://www.tensorflow.org/tutorials/image_retraining) to shorten the amount of time needed to train the entire model. This means we can take an existing model (that has been trained well on a related domain (here image classification) and retrain its final layer(s) to detect hands for us. Sweet!. Given that neural networks sometimes have thousands or millions of parameters that can take weeks or months to train, transfer learning helps shorten training time to possibly hours. Tensorflow does offer a few models (in the tensorflow [model zoo](https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md#coco-trained-models-coco-models)) and I chose to use the `ssd_mobilenet_v1_coco` model as my start point given it is currently (one of) the fastest models (read the SSD research [paper here](https://arxiv.org/pdf/1512.02325.pdf)). The training process can be done locally on your CPU machine which may take a while or better on a (cloud) GPU machine (which is what I did). For reference, training on my macbook pro (tensorflow compiled from source to take advantage of the mac's cpu architecture) the maximum speed I got was 5 seconds per step as opposed to the ~0.5 seconds per step I got with a GPU. For reference it would take about 12 days to run 200k steps on my mac (i7, 2.5GHz, 16GB) compared to ~5hrs on a GPU. > **Training on your own images**: Please use the [guide provided by Harrison from pythonprogramming](https://pythonprogramming.net/training-custom-objects-tensorflow-object-detection-api-tutorial/) on how to generate tfrecords given your label csv files and your images. The guide also covers how to start the training process if training locally. [see [here] (https://pythonprogramming.net/training-custom-objects-tensorflow-object-detection-api-tutorial/)]. If training in the cloud using a service like GCP, see the [guide here](https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/running_on_cloud.md). As the training process progresses, the expectation is that total loss (errors) gets reduced to its possible minimum (about a value of 1 or thereabout). By observing the tensorboard graphs for total loss(see image below), it should be possible to get an idea of when the training process is complete (total loss does not decrease with further iterations/steps). I ran my training job for 200k steps (took about 5 hours) and stopped at a total Loss (errors) value of 2.575.(In retrospect, I could have stopped the training at about 50k steps and gotten a similar total loss value). With tensorflow, you can also run an evaluation concurrently that assesses your model to see how well it performs on the test data. A commonly used metric for performance is mean average precision (mAP) which is single number used to summarize the area under the precision-recall curve. mAP is a measure of how well the model generates a bounding box that has at least a 50% overlap with the ground truth bounding box in our test dataset. For the hand detector trained here, the mAP value was **0.9686@0.5IOU**. mAP values range from 0-1, the higher the better. <img src="images/accuracy.jpg" width="100%"> Once training is completed, the trained inference graph (`frozen_inference_graph.pb`) is then exported (see the earlier referenced guides for how to do this) and saved in the `hand_inference_graph` folder. Now its time to do some interesting detection. ## Using the Detector to Detect/Track hands If you have not done this yet, please following the guide on installing [Tensorflow and the Tensorflow object detection api](https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/installation.md). This will walk you through setting up the tensorflow framework, cloning the tensorflow github repo and a guide on - Load the `frozen_inference_graph.pb` trained on the hands dataset as well as the corresponding label map. In this repo, this is done in the `utils/detector_utils.py` script by the `load_inference_graph` method. ```python detection_graph = tf.Graph() with detection_graph.as_default(): od_graph_def = tf.GraphDef() with tf.gfile.GFile(PATH_TO_CKPT, 'rb') as fid: serialized_graph = fid.read() od_graph_def.ParseFromString(serialized_graph) tf.import_graph_def(od_graph_def, name='') sess = tf.Session(graph=detection_graph) print("> ====== Hand Inference graph loaded.") ``` - Detect hands. In this repo, this is done in the `utils/detector_utils.py` script by the `detect_objects` method. ```python (boxes, scores, classes, num) = sess.run( [detection_boxes, detection_scores, detection_classes, num_detections], feed_dict={image_tensor: image_np_expanded}) ``` - Visualize detected bounding detection_boxes. In this repo, this is done in the `utils/detector_utils.py` script by the `draw_box_on_image` method. This repo contains two scripts that tie all these steps together. - detect_multi_threaded.py : A threaded implementation for reading camera video input detection and detecting. Takes a set of command line flags to set parameters such as `--display` (visualize detections), image parameters `--width` and `--height`, videe `--source` (0 for camera) etc. - detect_single_threaded.py : Same as above, but single threaded. This script works for video files by setting the video source parameter videe `--source` (path to a video file). ```cmd # load and run detection on video at path "videos/chess.mov" python detect_single_threaded.py --source videos/chess.mov ``` > Update: If you do have errors loading the frozen inference graph in this repo, feel free to generate a new graph that fits your TF version from the model-checkpoint in this repo. Use the [export_inference_graph.py](https://github.com/tensorflow/models/blob/master/research/object_detection/export_inference_graph.py) script provided in the tensorflow object detection api repo. More guidance on this [here](https://pythonprogramming.net/testing-custom-object-detector-tensorflow-object-detection-api-tutorial/?completed=/training-custom-objects-tensorflow-object-detection-api-tutorial/). ## Thoughts on Optimization. A few things that led to noticeable performance increases. - Threading: Turns out that reading images from a webcam is a heavy I/O event and if run on the main application thread can slow down the program. I implemented some good ideas from [Adrian Rosebuck](https://www.pyimagesearch.com/2017/02/06/faster-video-file-fps-with-cv2-videocapture-and-opencv/) on parrallelizing image capture across multiple worker threads. This mostly led to an FPS increase of about 5 points. - For those new to Opencv, images from the `cv2.read()` method return images in [BGR format](https://www.learnopencv.com/why-does-opencv-use-bgr-color-format/). Ensure you convert to RGB before detection (accuracy will be much reduced if you dont). ```python cv2.cvtColor(image_np, cv2.COLOR_BGR2RGB) ``` - Keeping your input image small will increase fps without any significant accuracy drop.(I used about 320 x 240 compared to the 1280 x 720 which my webcam provides). - Model Quantization. Moving from the current 32 bit to 8 bit can achieve up to 4x reduction in memory required to load and store models. One way to further speed up this model is to explore the use of [8-bit fixed point quantization](https://heartbeat.fritz.ai/8-bit-quantization-and-tensorflow-lite-speeding-up-mobile-inference-with-low-precision-a882dfcafbbd). Performance can also be increased by a clever combination of tracking algorithms with the already decent detection and this is something I am still experimenting with. Have ideas for optimizing better, please share! <img src="images/general.jpg" width="100%"> Note: The detector does reflect some limitations associated with the training set. This includes non-egocentric viewpoints, very noisy backgrounds (e.g in a sea of hands) and sometimes skin tone. There is opportunity to improve these with additional data. ## Integrating Multiple DNNs. One way to make things more interesting is to integrate our new knowledge of where "hands" are with other detectors trained to recognize other objects. Unfortunately, while our hand detector can in fact detect hands, it cannot detect other objects (a factor or how it is trained). To create a detector that classifies multiple different objects would mean a long involved process of assembling datasets for each class and a lengthy training process. > Given the above, a potential strategy is to explore structures that allow us **efficiently** interleave output form multiple pretrained models for various object classes and have them detect multiple objects on a single image. An example of this is with my primary use case where I am interested in understanding the position of objects on a table with respect to hands on same table. I am currently doing some work on a threaded application that loads multiple detectors and outputs bounding boxes on a single image. More on this soon.
lukasruff / Deep SVDDRepository for the Deep One-Class Classification ICML 2018 paper
abusufyanvu / 6S191 MIT DeepLearningMIT Introduction to Deep Learning (6.S191) Instructors: Alexander Amini and Ava Soleimany Course Information Summary Prerequisites Schedule Lectures Labs, Final Projects, Grading, and Prizes Software labs Gather.Town lab + Office Hour sessions Final project Paper Review Project Proposal Presentation Project Proposal Grading Rubric Past Project Proposal Ideas Awards + Categories Important Links and Emails Course Information Summary MIT's introductory course on deep learning methods with applications to computer vision, natural language processing, biology, and more! Students will gain foundational knowledge of deep learning algorithms and get practical experience in building neural networks in TensorFlow. Course concludes with a project proposal competition with feedback from staff and a panel of industry sponsors. Prerequisites We expect basic knowledge of calculus (e.g., taking derivatives), linear algebra (e.g., matrix multiplication), and probability (e.g., Bayes theorem) -- we'll try to explain everything else along the way! Experience in Python is helpful but not necessary. This class is taught during MIT's IAP term by current MIT PhD researchers. Listeners are welcome! Schedule Monday Jan 18, 2021 Lecture: Introduction to Deep Learning and NNs Lab: Lab 1A Tensorflow and building NNs from scratch Tuesday Jan 19, 2021 Lecture: Deep Sequence Modelling Lab: Lab 1B Music Generation using RNNs Wednesday Jan 20, 2021 Lecture: Deep Computer Vision Lab: Lab 2A Image classification and detection Thursday Jan 21, 2021 Lecture: Deep Generative Modelling Lab: Lab 2B Debiasing facial recognition systems Friday Jan 22, 2021 Lecture: Deep Reinforcement Learning Lab: Lab 3 pixel-to-control planning Monday Jan 25, 2021 Lecture: Limitations and New Frontiers Lab: Lab 3 continued Tuesday Jan 26, 2021 Lecture (part 1): Evidential Deep Learning Lecture (part 2): Bias and Fairness Lab: Work on final assignments Lab competition entries due at 11:59pm ET on Canvas! Lab 1, Lab 2, and Lab 3 Wednesday Jan 27, 2021 Lecture (part 1): Nigel Duffy, Ernst & Young Lecture (part 2): Kate Saenko, Boston University and MIT-IBM Watson AI Lab Lab: Work on final assignments Assignments due: Sign up for Final Project Competition Thursday Jan 28, 2021 Lecture (part 1): Sanja Fidler, U. Toronto, Vector Institute, and NVIDIA Lecture (part 2): Katherine Chou, Google Lab: Work on final assignments Assignments due: 1 page paper review (if applicable) Friday Jan 29, 2021 Lecture: Student project pitch competition Lab: Awards ceremony and prize giveaway Assignments due: Project proposals (if applicable) Lectures Lectures will be held starting at 1:00pm ET from Jan 18 - Jan 29 2021, Monday through Friday, virtually through Zoom. Current MIT students, faculty, postdocs, researchers, staff, etc. will be able to access the lectures during this two week period, synchronously or asynchronously, via the MIT Canvas course webpage (MIT internal only). Lecture recordings will be uploaded to the Canvas as soon as possible; students are not required to attend any lectures synchronously. Please see the Canvas for details on Zoom links. The public edition of the course will only be made available after completion of the MIT course. Labs, Final Projects, Grading, and Prizes Course will be graded during MIT IAP for 6 units under P/D/F grading. Receiving a passing grade requires completion of each software lab project (through honor code, with submission required to enter lab competitions), a final project proposal/presentation or written review of a deep learning paper (submission required), and attendance/lecture viewing (through honor code). Submission of a written report or presentation of a project proposal will ensure a passing grade. MIT students will be eligible for prizes and awards as part of the class competitions. There will be two parts to the competitions: (1) software labs and (2) final projects. More information is provided below. Winners will be announced on the last day of class, with thousands of dollars of prizes being given away! Software labs There are three TensorFlow software lab exercises for the course, designed as iPython notebooks hosted in Google Colab. Software labs can be found on GitHub: https://github.com/aamini/introtodeeplearning. These are self-paced exercises and are designed to help you gain practical experience implementing neural networks in TensorFlow. For registered MIT students, submission of lab materials is not necessary to get credit for the course or to pass the course. At the end of each software lab there will be task-associated materials to submit (along with instructions) for entry into the competitions, open to MIT students and affiliates during the IAP offering. This includes MIT students/affiliates who are taking the class as listeners -- you are eligible! These instructions are provided at the end of each of the labs. Completing these tasks and submitting your materials to Canvas will enter you into a per-lab competition. MIT students and affiliates will be eligible for prizes during the IAP offering; at the end of the course, prize-winners will be awarded with their prizes. All competition submissions are due on January 26 at 11:59pm ET to Canvas. For the software lab competitions, submissions will be judged on the basis of the following criteria: Strength and quality of final results (lab dependent) Soundness of implementation and approach Thoroughness and quality of provided descriptions and figures Gather.Town lab + Office Hour sessions After each day’s lecture, there will be open Office Hours in the class GatherTown, up until 3pm ET. An MIT email is required to log in and join the GatherTown. During these sessions, there will not be a walk through or dictation of the labs; the labs are designed to be self-paced and to be worked on on your own time. The GatherTown sessions will be hosted by course staff and are held so you can: Ask questions on course lectures, labs, logistics, project, or anything else; Work on the labs in the presence of classmates/TAs/instructors; Meet classmates to find groups for the final project; Group work time for the final project; Bring the class community together. Final project To satisfy the final project requirement for this course, students will have two options: (1) write a 1 page paper review (single-spaced) on a recent deep learning paper of your choice or (2) participate and present in the project proposal pitch competition. The 1 page paper review option is straightforward, we propose some papers within this document to help you get started, and you can satisfy a passing grade with this option -- you will not be eligible for the grand prizes. On the other hand, participation in the project proposal pitch competition will equivalently satisfy your course requirements but additionally make you eligible for the grand prizes. See the section below for more details and requirements for each of these options. Paper Review Students may satisfy the final project requirement by reading and reviewing a recent deep learning paper of their choosing. In the written review, students should provide both: 1) a description of the problem, technical approach, and results of the paper; 2) critical analysis and exposition of the limitations of the work and opportunities for future work. Reviews should be submitted on Canvas by Thursday Jan 28, 2021, 11:59:59pm Eastern Time (ET). Just a few paper options to consider... https://papers.nips.cc/paper/2017/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf https://papers.nips.cc/paper/2018/file/69386f6bb1dfed68692a24c8686939b9-Paper.pdf https://papers.nips.cc/paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf https://science.sciencemag.org/content/362/6419/1140 https://papers.nips.cc/paper/2018/file/0e64a7b00c83e3d22ce6b3acf2c582b6-Paper.pdf https://arxiv.org/pdf/1906.11829.pdf https://www.nature.com/articles/s42256-020-00237-3 https://pubmed.ncbi.nlm.nih.gov/32084340/ Project Proposal Presentation Keyword: proposal This is a 2 week course so we do not require results or working implementations! However, to win the top prizes, nice, clear results and implementations will demonstrate feasibility of your proposal which is something we look for! Logistics -- please read! You must sign up to present before 11:59:59pm Eastern Time (ET) on Wednesday Jan 27, 2021 Slides must be in a Google Slide before 11:59:59pm Eastern Time (ET) on Thursday Jan 28, 2021 Project groups can be between 1 and 5 people Listeners welcome To be eligible for a prize you must have at least 1 registered MIT student in your group Each participant will only be allowed to be in one group and present one project pitch Synchronous attendance on 1/29/21 is required to make the project pitch! 3 min presentation on your idea (we will be very strict with the time limits) Prizes! (see below) Sign up to Present here: by 11:59pm ET on Wednesday Jan 27 Once you sign up, make your slide in the following Google Slides; submit by midnight on Thursday Jan 28. Please specify the project group # on your slides!!! Things to Consider This doesn’t have to be a new deep learning method. It can just be an interesting application that you apply some existing deep learning method to. What problem are you solving? Are there use cases/applications? Why do you think deep learning methods might be suited to this task? How have people done it before? Is it a new task? If so, what are similar tasks that people have worked on? In what aspects have they succeeded or failed? What is your method of solving this problem? What type of model + architecture would you use? Why? What is the data for this task? Do you need to make a dataset or is there one publicly available? What are the characteristics of the data? Is it sparse, messy, imbalanced? How would you deal with that? Project Proposal Grading Rubric Project proposals will be evaluated by a panel of judges on the basis of the following three criteria: 1) novelty and impact; 2) technical soundness, feasibility, and organization, including quality of any presented results; 3) clarity and presentation. Each judge will award a score from 1 (lowest) to 5 (highest) for each of the criteria; the average score from each judge across these criteria will then be averaged with that of the other judges to provide the final score. The proposals with the highest final scores will be selected for prizes. Here are the guidelines for the criteria: Novelty and impact: encompasses the potential impact of the project idea, its novelty with respect to existing approaches. Why does the proposed work matter? What problem(s) does it solve? Why are these problems important? Technical soundness, feasibility, and organization: encompasses all technical aspects of the proposal. Do the proposed methodology and architecture make sense? Is the architecture the best suited for the proposed problem? Is deep learning the best approach for the problem? How realistic is it to implement the idea? Was there any implementation of the method? If results and data are presented, we will evaluate the strength of the results/data. Clarity and presentation: encompasses the delivery and quality of the presentation itself. Is the talk well organized? Are the slides aesthetically compelling? Is there a clear, well-delivered narrative? Are the problem and proposed method clearly presented? Past Project Proposal Ideas Recipe Generation with RNNs Can we compress videos with CNN + RNN? Music Generation with RNNs Style Transfer Applied to X GAN’s on a new modality Summarizing text/news articles Combining news articles about similar events Code or spec generation Multimodal speech → handwriting Generate handwriting based on keywords (i.e. cursive, slanted, neat) Predicting stock market trends Show language learners articles or videos at their level Transfer of writing style Chemical Synthesis with Recurrent Neural networks Transfer learning to learn something in a domain for which it’s hard or risky to gather data or do training RNNs to model some type of time series data Computer vision to coach sports players Computer vision system for safety brakes or warnings Use IBM Watson API to get the sentiment of your Facebook newsfeed Deep learning webcam to give wifi-access to friends or improve video chat in some way Domain-specific chatbot to help you perform a specific task Detect whether a signature is fraudulent Awards + Categories Final Project Awards: 1x NVIDIA RTX 3080 4x Google Home Max 3x Display Monitors Software Lab Awards: Bose headphones (Lab 1) Display monitor (Lab 2) Bebop drone (Lab 3) Important Links and Emails Course website: http://introtodeeplearning.com Course staff: introtodeeplearning-staff@mit.edu Piazza forum (MIT only): https://piazza.com/mit/spring2021/6s191 Canvas (MIT only): https://canvas.mit.edu/courses/8291 Software lab repository: https://github.com/aamini/introtodeeplearning Lab/office hour sessions (MIT only): https://gather.town/app/56toTnlBrsKCyFgj/MITDeepLearning
liznerski / FcddRepository for the Explainable Deep One-Class Classification paper
Sfedfcv / Redesigned PancakeSkip to content github / docs Code Issues 80 Pull requests 35 Discussions Actions Projects 2 Security Insights Merge branch 'main' into 1862-Add-Travis-CI-migration-table 1862-Add-Travis-CI-migration-table (#1869, Iixixi/ZachryTylerWood#102, THEBOLCK79/docs#1, sbnbhk/docs#1) @martin389 martin389 committed on Dec 9, 2020 2 parents 2f9ec0c + 1588f50 commit 1a56ed136914e522f3a23ecc2be1c49f479a1a6a Showing 501 changed files with 5,397 additions and 1,362 deletions. 2 .github/allowed-actions.js @@ -30,7 +30,7 @@ module.exports = [ 'rachmari/labeler@832d42ec5523f3c6d46e8168de71cd54363e3e2e', 'repo-sync/github-sync@3832fe8e2be32372e1b3970bbae8e7079edeec88', 'repo-sync/pull-request@33777245b1aace1a58c87a29c90321aa7a74bd7d', 'rtCamp/action-slack-notify@e17352feaf9aee300bf0ebc1dfbf467d80438815', 'someimportantcompany/github-actions-slack-message@0b470c14b39da4260ed9e3f9a4f1298a74ccdefd', 'tjenkinson/gh-action-auto-merge-dependency-updates@cee2ac0', 'EndBug/add-and-commit@9358097a71ad9fb9e2f9624c6098c89193d83575' ] 72 .github/workflows/confirm-internal-staff-work-in-docs.yml @@ -0,0 +1,72 @@ name: Confirm internal staff meant to post in public on: issues: types: - opened - reopened - transferred pull_request_target: types: - opened - reopened jobs: check-team-membership: runs-on: ubuntu-latest continue-on-error: true if: github.repository == 'github/docs' steps: - uses: actions/github-script@626af12fe9a53dc2972b48385e7fe7dec79145c9 with: github-token: ${{ secrets.DOCUBOT_FR_PROJECT_BOARD_WORKFLOWS_REPO_ORG_READ_SCOPES }} script: | // Only perform this action with GitHub employees try { await github.teams.getMembershipForUserInOrg({ org: 'github', team_slug: 'employees', username: context.payload.sender.login, }); } catch(err) { // An error will be thrown if the user is not a GitHub employee // If a user is not a GitHub employee, we should stop here and // Not send a notification return } // Don't perform this action with Docs team members try { await github.teams.getMembershipForUserInOrg({ org: 'github', team_slug: 'docs', username: context.payload.sender.login, }); // If the user is a Docs team member, we should stop here and not send // a notification return } catch(err) { // An error will be thrown if the user is not a Docs team member // If a user is not a Docs team member we should continue and send // the notification } const issueNo = context.number || context.issue.number // Create an issue in our private repo await github.issues.create({ owner: 'github', repo: 'docs-internal', title: `@${context.payload.sender.login} confirm that \#${issueNo} should be in the public github/docs repo`, body: `@${context.payload.sender.login} opened https://github.com/github/docs/issues/${issueNo} publicly in the github/docs repo, instead of the private github/docs-internal repo.\n\n@${context.payload.sender.login}, please confirm that this belongs in the public repo and that no sensitive information was disclosed by commenting below and closing the issue.\n\nIf this was not intentional and sensitive information was shared, please delete https://github.com/github/docs/issues/${issueNo} and notify us in the \#docs-open-source channel.\n\nThanks! \n\n/cc @github/docs @github/docs-engineering` }); throw new Error('A Hubber opened an issue on the public github/docs repo'); - name: Send Slack notification if a GitHub employee who isn't on the docs team opens an issue in public if: ${{ failure() && github.repository == 'github/docs' }} uses: someimportantcompany/github-actions-slack-message@0b470c14b39da4260ed9e3f9a4f1298a74ccdefd with: channel: ${{ secrets.DOCS_OPEN_SOURCE_SLACK_CHANNEL_ID }} bot-token: ${{ secrets.SLACK_DOCS_BOT_TOKEN }} text: <@${{github.actor}}> opened https://github.com/github/docs/issues/${{ github.event.number || github.event.issue.number }} publicly on the github/docs repo instead of the private github/docs-internal repo. They have been notified via a new issue in the github/docs-internal repo to confirm this was intentional. 15 .github/workflows/js-lint.yml @@ -10,23 +10,8 @@ on: - translations jobs: see_if_should_skip: runs-on: ubuntu-latest outputs: should_skip: ${{ steps.skip_check.outputs.should_skip }} steps: - id: skip_check uses: fkirc/skip-duplicate-actions@36feb0d8d062137530c2e00bd278d138fe191289 with: cancel_others: 'false' github_token: ${{ github.token }} paths: '["**/*.js", "package*.json", ".github/workflows/js-lint.yml", ".eslint*"]' lint: runs-on: ubuntu-latest needs: see_if_should_skip if: ${{ needs.see_if_should_skip.outputs.should_skip != 'true' }} steps: - name: Check out repo uses: actions/checkout@5a4ac9002d0be2fb38bd78e4b4dbde5606d7042f 13 .github/workflows/repo-freeze-reminders.yml @@ -14,11 +14,10 @@ jobs: if: github.repository == 'github/docs-internal' steps: - name: Send Slack notification if repo is frozen uses: someimportantcompany/github-actions-slack-message@0b470c14b39da4260ed9e3f9a4f1298a74ccdefd if: ${{ env.FREEZE == 'true' }} uses: rtCamp/action-slack-notify@e17352feaf9aee300bf0ebc1dfbf467d80438815 env: SLACK_WEBHOOK: ${{ secrets.DOCS_ALERTS_SLACK_WEBHOOK }} SLACK_USERNAME: docs-repo-sync SLACK_ICON_EMOJI: ':freezing_face:' SLACK_COLOR: '#51A0D5' # Carolina Blue SLACK_MESSAGE: All repo-sync runs will fail for ${{ github.repository }} because the repo is currently frozen! with: channel: ${{ secrets.DOCS_ALERTS_SLACK_CHANNEL_ID }} bot-token: ${{ secrets.SLACK_DOCS_BOT_TOKEN }} color: info text: All repo-sync runs will fail for ${{ github.repository }} because the repo is currently frozen! 54 .github/workflows/repo-sync-stalls.yml @@ -0,0 +1,54 @@ name: Repo Sync Stalls on: workflow_dispatch: schedule: - cron: '*/30 * * * *' jobs: check-freezer: name: Check for deployment freezes runs-on: ubuntu-latest steps: - name: Exit if repo is frozen if: ${{ env.FREEZE == 'true' }} run: | echo 'The repo is currently frozen! Exiting this workflow.' exit 1 # prevents further steps from running repo-sync-stalls: runs-on: ubuntu-latest steps: - name: Check if repo sync is stalled uses: actions/github-script@626af12fe9a53dc2972b48385e7fe7dec79145c9 with: github-token: ${{ secrets.DOCUBOT_FR_PROJECT_BOARD_WORKFLOWS_REPO_ORG_READ_SCOPES }} script: | let pulls; const owner = context.repo.owner const repo = context.repo.repo try { pulls = await github.pulls.list({ owner: owner, repo: repo, head: `${owner}:repo-sync`, state: 'open' }); } catch(err) { throw err return } pulls.data.forEach(pr => { const timeDelta = Date.now() - Date.parse(pr.created_at); const minutesOpen = timeDelta / 1000 / 60; if (minutesOpen > 30) { core.setFailed('Repo sync appears to be stalled') } }) - name: Send Slack notification if workflow fails uses: someimportantcompany/github-actions-slack-message@0b470c14b39da4260ed9e3f9a4f1298a74ccdefd if: failure() with: channel: ${{ secrets.DOCS_ALERTS_SLACK_CHANNEL_ID }} bot-token: ${{ secrets.SLACK_DOCS_BOT_TOKEN }} color: failure text: Repo sync appears to be stalled for ${{github.repository}}. See https://github.com/${{github.repository}}/pulls?q=is%3Apr+is%3Aopen+repo+sync 16 .github/workflows/repo-sync.yml @@ -7,6 +7,7 @@ name: Repo Sync on: workflow_dispatch: schedule: - cron: '*/15 * * * *' # every 15 minutes @@ -70,11 +71,10 @@ jobs: number: ${{ steps.find-pull-request.outputs.number }} - name: Send Slack notification if workflow fails uses: rtCamp/action-slack-notify@e17352feaf9aee300bf0ebc1dfbf467d80438815 if: ${{ failure() }} env: SLACK_WEBHOOK: ${{ secrets.DOCS_ALERTS_SLACK_WEBHOOK }} SLACK_USERNAME: docs-repo-sync SLACK_ICON_EMOJI: ':ohno:' SLACK_COLOR: '#B90E0A' # Crimson SLACK_MESSAGE: The last repo-sync run for ${{github.repository}} failed. See https://github.com/${{github.repository}}/actions?query=workflow%3A%22Repo+Sync%22 uses: someimportantcompany/github-actions-slack-message@0b470c14b39da4260ed9e3f9a4f1298a74ccdefd if: failure() with: channel: ${{ secrets.DOCS_ALERTS_SLACK_CHANNEL_ID }} bot-token: ${{ secrets.SLACK_DOCS_BOT_TOKEN }} color: failure text: The last repo-sync run for ${{github.repository}} failed. See https://github.com/${{github.repository}}/actions?query=workflow%3A%22Repo+Sync%22 10 .github/workflows/sync-algolia-search-indices.yml @@ -33,8 +33,10 @@ jobs: GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} run: npm run sync-search - name: Send slack notification if workflow run fails uses: rtCamp/action-slack-notify@e17352feaf9aee300bf0ebc1dfbf467d80438815 uses: someimportantcompany/github-actions-slack-message@0b470c14b39da4260ed9e3f9a4f1298a74ccdefd if: failure() env: SLACK_WEBHOOK: ${{ secrets.DOCS_ALERTS_SLACK_WEBHOOK }} SLACK_MESSAGE: The last Algolia workflow run for ${{github.repository}} failed. Search actions for `workflow:Algolia` with: channel: ${{ secrets.DOCS_ALERTS_SLACK_CHANNEL_ID }} bot-token: ${{ secrets.SLACK_DOCS_BOT_TOKEN }} color: failure text: The last Algolia workflow run for ${{github.repository}} failed. Search actions for `workflow:Algolia` 15 .github/workflows/yml-lint.yml @@ -10,23 +10,8 @@ on: - translations jobs: see_if_should_skip: runs-on: ubuntu-latest outputs: should_skip: ${{ steps.skip_check.outputs.should_skip }} steps: - id: skip_check uses: fkirc/skip-duplicate-actions@36feb0d8d062137530c2e00bd278d138fe191289 with: cancel_others: 'false' github_token: ${{ github.token }} paths: '["**/*.yml", "**/*.yaml", "package*.json", ".github/workflows/yml-lint.yml"]' lint: runs-on: ubuntu-latest needs: see_if_should_skip if: ${{ needs.see_if_should_skip.outputs.should_skip != 'true' }} steps: - name: Check out repo uses: actions/checkout@5a4ac9002d0be2fb38bd78e4b4dbde5606d7042f 4 README.md @@ -28,7 +28,7 @@ If you've found a problem, you can open an issue using a [template](https://gith #### Solve an issue If you have a solution to one of the open issues, you will need to fork the repository and submit a PR using the [template](https://github.com/github/docs/blob/main/CONTRIBUTING.md#pull-request-template) that is visible automatically in the pull request body. For more details about this process, please check out [Getting Started with Contributing](/CONTRIBUTING.md). If you have a solution to one of the open issues, you will need to fork the repository and submit a pull request using the [template](https://github.com/github/docs/blob/main/CONTRIBUTING.md#pull-request-template) that is visible automatically in the pull request body. For more details about this process, please check out [Getting Started with Contributing](/CONTRIBUTING.md). #### Join us in discussions @@ -50,6 +50,8 @@ There are a few more things to know when you're getting started with this repo: In addition to the README you're reading right now, this repo includes other READMEs that describe the purpose of each subdirectory in more detail: - [content/README.md](content/README.md) - [content/graphql/README.md](content/graphql/README.md) - [content/rest/README.md](content/rest/README.md) - [contributing/README.md](contributing/README.md) - [data/README.md](data/README.md) - [data/reusables/README.md](data/reusables/README.md) BIN +164 KB assets/images/help/classroom/assignment-group-hero.png Binary file not shown. BIN +75.5 KB assets/images/help/classroom/assignment-ide-go-grant-access-button.png Binary file not shown. BIN +175 KB assets/images/help/classroom/assignment-individual-hero.png Binary file not shown. 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You should see "Hello Mona the Octocat" or the name you used for the `who-to-greet` input and the timestamp printed in the log. From your repository, click the **Actions** tab, and select the latest workflow run. {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@3.0" %}Under **Jobs** or in the visualization graph, click **A job to say hello**. {% endif %}You should see "Hello Mona the Octocat" or the name you used for the `who-to-greet` input and the timestamp printed in the log. {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@3.0" %}  {% else %}  {% endif %} 6 content/actions/creating-actions/creating-a-javascript-action.md @@ -261,9 +261,11 @@ jobs: ``` {% endraw %} From your repository, click the **Actions** tab, and select the latest workflow run. You should see "Hello Mona the Octocat" or the name you used for the `who-to-greet` input and the timestamp printed in the log. From your repository, click the **Actions** tab, and select the latest workflow run. {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@3.0" %}Under **Jobs** or in the visualization graph, click **A job to say hello**. {% endif %}You should see "Hello Mona the Octocat" or the name you used for the `who-to-greet` input and the timestamp printed in the log. {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@2.22" %} {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@3.0" %}  {% elsif currentVersion ver_gt "enterprise-server@2.22" %}  {% else %}  4 content/actions/guides/about-packaging-with-github-actions.md @@ -25,7 +25,11 @@ Creating a package at the end of a continuous integration workflow can help duri Now, when reviewing a pull request, you'll be able to look at the workflow run and download the artifact that was produced. {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@3.0" %}  {% else %}  {% endif %} This will let you run the code in the pull request on your machine, which can help with debugging or testing the pull request. 4 content/actions/guides/building-and-testing-powershell.md @@ -60,7 +60,11 @@ jobs: * `run: Test-Path resultsfile.log` - Check whether a file called `resultsfile.log` is present in the repository's root directory. * `Should -Be $true` - Uses Pester to define an expected result. If the result is unexpected, then {% data variables.product.prodname_actions %} flags this as a failed test. For example: {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@3.0" %}  {% else %}  {% endif %} * `Invoke-Pester Unit.Tests.ps1 -Passthru` - Uses Pester to execute tests defined in a file called `Unit.Tests.ps1`. For example, to perform the same test described above, the `Unit.Tests.ps1` will contain the following: ``` 7 content/actions/guides/storing-workflow-data-as-artifacts.md @@ -108,8 +108,6 @@ jobs: path: output/test/code-coverage.html ```  {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@2.22" %} ### Configuring a custom artifact retention period @@ -238,7 +236,12 @@ jobs: echo The result is $value ``` The workflow run will archive any artifacts that it generated. For more information on downloading archived artifacts, see "[Downloading workflow artifacts](/actions/managing-workflow-runs/downloading-workflow-artifacts)." {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@3.0" %}  {% else %}  {% endif %} {% if currentVersion == "free-pro-team@latest" %} 8 content/actions/index.md @@ -68,18 +68,18 @@ versions: <h2 class="mb-2 font-mktg h1">Code examples</h2> <div class="pr-lg-3 mb-5 mt-3"> <input class="js-code-example-filter input-lg py-2 px-3 col-12 col-lg-8 form-control" placeholder="Search code examples" type="search" autocomplete="off" aria-label="Search code examples"/> <input class="js-filter-card-filter input-lg py-2 px-3 col-12 col-lg-8 form-control" placeholder="Search code examples" type="search" autocomplete="off" aria-label="Search code examples"/> </div> <div class="d-flex flex-wrap gutter"> {% render 'code-example-card' for actionsCodeExamples as example %} </div> <button class="js-code-example-show-more btn btn-outline float-right">Show more {% octicon "arrow-right" %}</button> <button class="js-filter-card-show-more btn btn-outline float-right">Show more {% octicon "arrow-right" %}</button> <div class="js-code-example-no-results d-none py-4 text-center text-gray font-mktg"> <div class="js-filter-card-no-results d-none py-4 text-center text-gray font-mktg"> <div class="mb-3">{% octicon "search" width="24" %}</div> <h3 class="text-normal">Sorry, there is no result for <strong class="js-code-example-filter-value"></strong></h3> <h3 class="text-normal">Sorry, there is no result for <strong class="js-filter-card-value"></strong></h3> <p class="my-3 f4">It looks like we don't have an example that fits your filter.<br>Try another filter or add your code example</p> <a href="https://github.com/github/docs/blob/main/data/variables/action_code_examples.yml">Learn how to add a code example {% octicon "arrow-right" %}</a> </div> 11 content/actions/learn-github-actions/introduction-to-github-actions.md @@ -204,7 +204,7 @@ In this diagram, you can see the workflow file you just created and how the {% d ### Viewing the job's activity Once your job has started running, you can view each step's activity on {% data variables.product.prodname_dotcom %}. Once your job has started running, you can {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@3.0" %}see a visualization graph of the run's progress and {% endif %}view each step's activity on {% data variables.product.prodname_dotcom %}. {% data reusables.repositories.navigate-to-repo %} 1. Under your repository name, click **Actions**. @@ -213,7 +213,14 @@ Once your job has started running, you can view each step's activity on {% data  1. Under "Workflow runs", click the name of the run you want to see.  {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@2.22" %} {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@3.0" %} 1. Under **Jobs** or in the visualization graph, click the job you want to see.  {% endif %} {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@3.0" %} 1. View the results of each step.  {% elsif currentVersion ver_gt "enterprise-server@2.22" %} 1. Click on the job name to see the results of each step.  {% else %} 7 content/actions/managing-workflow-runs/canceling-a-workflow.md @@ -17,9 +17,14 @@ versions: {% data reusables.repositories.navigate-to-repo %} {% data reusables.repositories.actions-tab %} {% data reusables.repositories.navigate-to-workflow %} {% data reusables.repositories.view-run %} 1. From the list of workflow runs, click the name of the `queued` or `in progress` run that you want to cancel.  1. In the upper-right corner of the workflow, click **Cancel workflow**. {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@3.0" %}  {% else %}  {% endif %} ### Steps {% data variables.product.prodname_dotcom %} takes to cancel a workflow run 4 content/actions/managing-workflow-runs/downloading-workflow-artifacts.md @@ -20,4 +20,8 @@ versions: {% data reusables.repositories.navigate-to-workflow %} {% data reusables.repositories.view-run %} 1. Under **Artifacts**, click the artifact you want to download. {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@3.0" %}  {% else %}  {% endif %} 1 content/actions/managing-workflow-runs/index.md @@ -18,6 +18,7 @@ versions: {% data reusables.actions.enterprise-beta %} {% data reusables.actions.enterprise-github-hosted-runners %} {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@3.0" %}{% link_in_list /using-the-visualization-graph %}{% endif %} {% link_in_list /viewing-workflow-run-history %} {% link_in_list /using-workflow-run-logs %} {% link_in_list /manually-running-a-workflow %} 3 content/actions/managing-workflow-runs/re-running-a-workflow.md @@ -16,5 +16,4 @@ versions: {% data reusables.repositories.actions-tab %} {% data reusables.repositories.navigate-to-workflow %} {% data reusables.repositories.view-run %} 1. In the upper-right corner of the workflow, use the **Re-run jobs** drop-down menu, and select **Re-run all jobs**.  1. In the upper-right corner of the workflow, use the **Re-run jobs** drop-down menu, and select **Re-run all jobs**.{% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@3.0" %}{% else %}{% endif %} 4 content/actions/managing-workflow-runs/removing-workflow-artifacts.md @@ -27,7 +27,11 @@ versions: {% data reusables.repositories.navigate-to-workflow %} {% data reusables.repositories.view-run %} 1. Under **Artifacts**, click {% octicon "trashcan" aria-label="The trashcan icon" %} next to the artifact you want to remove. {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@3.0" %}  {% else %}  {% endif %} {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@2.22" %} ### Setting the retention period for an artifact 23 content/actions/managing-workflow-runs/using-the-visualization-graph.md @@ -0,0 +1,23 @@ --- title: Using the visualization graph intro: Every workflow run generates a real-time graph that illustrates the run progress. You can use this graph to monitor and debug workflows. product: '{% data reusables.gated-features.actions %}' versions: free-pro-team: '*' enterprise-server: '>=3.1' --- {% data reusables.actions.enterprise-beta %} {% data reusables.actions.visualization-beta %} {% data reusables.actions.enterprise-github-hosted-runners %} {% data reusables.repositories.navigate-to-repo %} {% data reusables.repositories.actions-tab %} {% data reusables.repositories.navigate-to-workflow %} {% data reusables.repositories.view-run %} 1. The graph displays each job in the workflow. An icon to the left of the job name indicates the status of the job. Lines between jobs indicate dependencies.  2. Click on a job to view the job log.  18 content/actions/managing-workflow-runs/using-workflow-run-logs.md @@ -45,7 +45,11 @@ You can search the build logs for a particular step. When you search logs, only {% data reusables.repositories.navigate-to-job-superlinter %} {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@2.22" %} 1. In the upper-right corner of the log output, in the **Search logs** search box, type a search query. {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@3.0" %}  {% else %}  {% endif %} {% else %} 1. To expand each step you want to include in your search, click the step.  @@ -63,8 +67,12 @@ You can download the log files from your workflow run. You can also download a w {% data reusables.repositories.view-run-superlinter %} {% data reusables.repositories.navigate-to-job-superlinter %} {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@2.22" %} 1. In the upper right corner, click {% octicon "kebab-horizontal" aria-label="The horizontal kebab icon" %} and select **Download log archive**. 1. In the upper right corner, click {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@3.0" %}{% octicon "gear" aria-label="The gear icon" %}{% else %}{% octicon "kebab-horizontal" aria-label="The horizontal kebab icon" %}{% endif %} and select **Download log archive**. {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@3.0" %}  {% else %}  {% endif %} {% else %} 1. In the upper right corner, click {% octicon "kebab-horizontal" aria-label="The horizontal kebab icon" %} and select **Download log archive**.  @@ -80,9 +88,17 @@ You can delete the log files from your workflow run. {% data reusables.repositor {% data reusables.repositories.view-run-superlinter %} {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@2.22" %} 1. In the upper right corner, click {% octicon "kebab-horizontal" aria-label="The horizontal kebab icon" %}. {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@3.0" %}  {% else %}  {% endif %} 2. To delete the log files, click the **Delete all logs** button and review the confirmation prompt. {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@3.0" %}  {% else %}  {% endif %} After deleting logs, the **Delete all logs** button is removed to indicate that no log files remain in the workflow run. {% else %} 1. In the upper right corner, click {% octicon "kebab-horizontal" aria-label="The horizontal kebab icon" %}. 2 content/actions/managing-workflow-runs/viewing-job-execution-time.md @@ -15,7 +15,7 @@ Billable job execution minutes are only shown for jobs run on private repositori {% data reusables.repositories.actions-tab %} {% data reusables.repositories.navigate-to-workflow %} {% data reusables.repositories.view-run %} 1. Under the job summary, you can view the job's execution time. To view the billable job execution time, click **Run and billable time details**. 1. Under the job summary, you can view the job's execution time. To view details about the billable job execution time, click the time under **Billable time**.  {% note %} 5 content/actions/quickstart.md @@ -60,8 +60,13 @@ Committing the workflow file in your repository triggers the `push` event and ru {% data reusables.repositories.actions-tab %} {% data reusables.repositories.navigate-to-workflow-superlinter %} {% data reusables.repositories.view-run-superlinter %} {% if currentVersion == "free-pro-team@latest" or currentVersion ver_gt "enterprise-server@3.0" %} 1. Under **Jobs** or in the visualization graph, click the **Lint code base** job.  {% else %} 1. In the left sidebar, click the **Lint code base** job.  {% endif %} {% data reusables.repositories.view-failed-job-results-superlinter %} ### More starter workflows 49 content/developers/github-marketplace/about-github-marketplace.md @@ -1,6 +1,6 @@ --- title: About GitHub Marketplace intro: 'Learn the basics to prepare your app for review before joining {% data variables.product.prodname_marketplace %}.' intro: 'Learn about {% data variables.product.prodname_marketplace %} where you can share your apps and actions publicly with all {% data variables.product.product_name %} users.' redirect_from: - /apps/marketplace/getting-started/ - /marketplace/getting-started @@ -14,52 +14,41 @@ versions: {% data reusables.actions.actions-not-verified %} To learn about publishing {% data variables.product.prodname_actions %} in the {% data variables.product.prodname_marketplace %}, see "[Publishing actions in GitHub Marketplace](/actions/creating-actions/publishing-actions-in-github-marketplace)." To learn about publishing {% data variables.product.prodname_actions %} in {% data variables.product.prodname_marketplace %}, see "[Publishing actions in GitHub Marketplace](/actions/creating-actions/publishing-actions-in-github-marketplace)." ### Apps You can list verified and unverified apps in {% data variables.product.prodname_marketplace %}. Unverified apps do not go through the security, testing, and verification cycle {% data variables.product.prodname_dotcom %} requires for verified apps. Anyone can share their apps with other users on {% data variables.product.prodname_marketplace %} but only listings that are verified by {% data variables.product.company_short %} can include paid plans. For more information, see "[About verified creators](/developers/github-marketplace/about-verified-creators)." Verified apps have a green badge in {% data variables.product.prodname_marketplace %}. Unverified apps have a grey badge next to their listing and are only available as free apps. If you're interested in creating an app for {% data variables.product.prodname_marketplace %}, but you're new to {% data variables.product.prodname_github_apps %} or {% data variables.product.prodname_oauth_app %}s, see "[Building {% data variables.product.prodname_github_apps %}](/developers/apps/building-github-apps)" or "[Building {% data variables.product.prodname_oauth_app %}s](/developers/apps/building-oauth-apps)."  If you're interested in creating an app for {% data variables.product.prodname_marketplace %}, but you're new to {% data variables.product.prodname_github_apps %} and {% data variables.product.prodname_oauth_app %}s, see "[Building apps](/apps/)." {% data reusables.marketplace.github_apps_preferred %}, although you can list both OAuth and {% data variables.product.prodname_github_app %}s in {% data variables.product.prodname_marketplace %}. See "[Differences between GitHub and OAuth apps](/apps/differences-between-apps/)" for more details. To learn more about switching from OAuth to {% data variables.product.prodname_github_apps %}, see [Migrating OAuth Apps to {% data variables.product.prodname_github_app %}s](/apps/migrating-oauth-apps-to-github-apps/). {% data reusables.marketplace.github_apps_preferred %}, although you can list both OAuth and {% data variables.product.prodname_github_app %}s in {% data variables.product.prodname_marketplace %}. For more information, see "[Differences between {% data variables.product.prodname_github_apps %} and {% data variables.product.prodname_oauth_app %}s](/apps/differences-between-apps/)" and "[Migrating {% data variables.product.prodname_oauth_app %}s to {% data variables.product.prodname_github_apps %}](/apps/migrating-oauth-apps-to-github-apps/)." If you have questions about {% data variables.product.prodname_marketplace %}, please contact {% data variables.contact.contact_support %} directly. #### Unverified Apps Unverified apps do not need to meet the "[Requirements for listing an app on {% data variables.product.prodname_marketplace %}](/marketplace/getting-started/requirements-for-listing-an-app-on-github-marketplace/)" or go through the "[Security review process](/marketplace/getting-started/security-review-process/)". {% data reusables.marketplace.unverified-apps %} Having a published paid plan will prevent you from being able to submit an unverified app. You must remove paid plans or keep them in draft mode before publishing an unverified app. To list your unverified app in {% data variables.product.prodname_marketplace %}, you only need to create a "[Listing on {% data variables.product.prodname_marketplace %}](/marketplace/listing-on-github-marketplace/)" and submit it as an unverified listing. {% data reusables.marketplace.launch-with-free %} ### Publishing an app to {% data variables.product.prodname_marketplace %} #### Verified Apps When you have finished creating your app, you can share it with other users by publishing it to {% data variables.product.prodname_marketplace %}. In summary, the process is: If you've already built an app and you're interested in submitting a verified listing in {% data variables.product.prodname_marketplace %}, start here: 1. Review your app carefully to ensure that it will behave as expected in other repositories and that it follows best practice guidelines. For more information, see "[Security best practices for apps](/developers/github-marketplace/security-best-practices-for-apps)" and "[Requirements for listing an app](/developers/github-marketplace/requirements-for-listing-an-app#best-practice-for-customer-experience)." 1. [Getting started with {% data variables.product.prodname_marketplace %}](/marketplace/getting-started/)<br/>Learn about requirements, guidelines, and the app submission process. 1. Add webhook events to the app to track user billing requests. For more information about the {% data variables.product.prodname_marketplace %} API, webhook events, and billing requests, see "[Using the {% data variables.product.prodname_marketplace %} API in your app](/developers/github-marketplace/using-the-github-marketplace-api-in-your-app)." 1. [Integrating with the {% data variables.product.prodname_marketplace %} API](/marketplace/integrating-with-the-github-marketplace-api/)<br/>Before you can list your app on {% data variables.product.prodname_marketplace %}, you'll need to integrate billing flows using the {% data variables.product.prodname_marketplace %} API and webhook events. 1. Create a draft {% data variables.product.prodname_marketplace %} listing. For more information, see "[Drafting a listing for your app](/developers/github-marketplace/drafting-a-listing-for-your-app)." 1. [Listing on {% data variables.product.prodname_marketplace %}](/marketplace/listing-on-github-marketplace/) <br/>Create a draft {% data variables.product.prodname_marketplace %} listing, configure webhook settings, and set up pricing plans. 1. Add a pricing plan. For more information, see "[Setting pricing plans for your listing](/developers/github-marketplace/setting-pricing-plans-for-your-listing)." 1. [Selling your app](/marketplace/selling-your-app/)<br/>Learn about pricing plans, billing cycles, and how to receive payment from {% data variables.product.prodname_dotcom %} for your app. 1. Check whether your app meets the requirements for listing on {% data variables.product.prodname_marketplace %} as a free or a paid app. For more information, see "[Requirements for listing an app](/developers/github-marketplace/requirements-for-listing-an-app)." 1. [{% data variables.product.prodname_marketplace %} Insights](/marketplace/github-marketplace-insights/)<br/>See how your app is performing in {% data variables.product.prodname_marketplace %}. You can use metrics collected by {% data variables.product.prodname_dotcom %} to guide your marketing campaign and be successful in {% data variables.product.prodname_marketplace %}. 1. Read and accept the terms of the "[{% data variables.product.prodname_marketplace %} Developer Agreement](/articles/github-marketplace-developer-agreement/)." 1. [{% data variables.product.prodname_marketplace %} transactions](/marketplace/github-marketplace-transactions/)<br/>Download and view transaction data for your {% data variables.product.prodname_marketplace %} listing. 1. Submit your listing for publication in {% data variables.product.prodname_marketplace %}, requesting verification if you want to sell the app. For more information, see "[Submitting your listing for publication](/developers/github-marketplace/submitting-your-listing-for-publication)." ### Reviewing your app An onboarding expert will contact you with any questions or further steps. For example, if you have added a paid plan, you will need to complete the verification process and complete financial onboarding. As soon as your listing is approved the app is published to {% data variables.product.prodname_marketplace %}. We want to make sure that the apps offered on {% data variables.product.prodname_marketplace %} are safe, secure, and well tested. The {% data variables.product.prodname_marketplace %} onboarding specialists will review your app to ensure that it meets all requirements. Follow the guidelines in these articles before submitting your app: ### Seeing how your app is performing You can access metrics and transactions for your listing. For more information, see: * [Requirements for listing an app on {% data variables.product.prodname_marketplace %}](/marketplace/getting-started/requirements-for-listing-an-app-on-github-marketplace/) * [Security review process](/marketplace/getting-started/security-review-process/) - "[Viewing metrics for your listing](/developers/github-marketplace/viewing-metrics-for-your-listing)" - "[Viewing transactions for your listing](/developers/github-marketplace/viewing-transactions-for-your-listing)" 43 content/developers/github-marketplace/about-verified-creators.md @@ -0,0 +1,43 @@ --- title: About verified creators intro: 'Each organization that wants to sell apps on {% data variables.product.prodname_marketplace %} must follow a verification process. Their identity is checked and their billing process reviewed.' versions: free-pro-team: '*' --- ### About verified creators A verified creator is an organization that {% data variables.product.company_short %} has checked. Anyone can share their apps with other users on {% data variables.product.prodname_marketplace %} but only organizations that are verified by {% data variables.product.company_short %} can sell apps. For more information about organizations, see "[About organizations](/github/setting-up-and-managing-organizations-and-teams/about-organizations)." The verification process aims to protect users. For example, it verifies the seller's identity, checks that their {% data variables.product.product_name %} organization is set up securely, and that they can be contacted for support. After passing the verification checks, any apps that the organization lists on {% data variables.product.prodname_marketplace %} are shown with a verified creator badge {% octicon "verified" aria-label="Verified creator badge" %}. The organization can now add paid plans to any of their apps. Each app with a paid plan also goes through a financial onboarding process to check that it's set up to handle billing correctly.  In addition to the verified creator badge, you'll also see badges for unverified and verified apps. These apps were published using the old method for verifying individual apps.  For information on finding apps to use, see "[Searching {% data variables.product.prodname_marketplace %}](/github/searching-for-information-on-github/searching-github-marketplace)." ### About the verification process The first time you request verification for a listing of one of your apps, you will enter the verification process. An onboarding expert will guide you through the process. This includes checking: - Profile information - The basic profile information is populated accurately and appropriately. - Security - The organization has enabled two-factor authentication. - Verified domain - The organization has verified the domain of the site URL. - Purchase webhook event - The event is handled correctly by the app. When your organization is verified, all your apps are shown with a verified creator badge. You are now able to offer paid plans for any of your apps. For more information about the requirements for listing an app on {% data variables.product.prodname_marketplace %}, see "[Requirements for listing an app on {% data variables.product.prodname_marketplace %}](/marketplace/getting-started/requirements-for-listing-an-app-on-github-marketplace/)." {% data reusables.marketplace.app-transfer-to-org-for-verification %} For information on how to do this, see: "[Submitting your listing for publication](/developers/github-marketplace/submitting-your-listing-for-publication#transferring-an-app-to-an-organization-before-you-submit)." {% note %} **Note:** This verification process for apps replaces the previous process where individual apps were verified. The current process is similar to the verification process for actions. If you have apps that were verified under the old process, these will not be affected by the changes. The {% data variables.product.prodname_marketplace %} team will contact you with details of how to migrate to organization-based verification. {% endnote %} 12 content/developers/github-marketplace/billing-customers.md @@ -13,17 +13,17 @@ versions: ### Understanding the billing cycle Customers can choose a monthly or yearly billing cycle when they purchase your app. All changes customers make to the billing cycle and plan selection will trigger a `marketplace_purchase` event. You can refer to the `marketplace_purchase` webhook payload to see which billing cycle a customer selects and when the next billing date begins (`effective_date`). For more information about webhook payloads, see "[{% data variables.product.prodname_marketplace %} webhook events](/marketplace/integrating-with-the-github-marketplace-api/github-marketplace-webhook-events/)." Customers can choose a monthly or yearly billing cycle when they purchase your app. All changes customers make to the billing cycle and plan selection will trigger a `marketplace_purchase` event. You can refer to the `marketplace_purchase` webhook payload to see which billing cycle a customer selects and when the next billing date begins (`effective_date`). For more information about webhook payloads, see "[Webhook events for the {% data variables.product.prodname_marketplace %} API](/developers/github-marketplace/webhook-events-for-the-github-marketplace-api)." ### Providing billing services in your app's UI Customers must be able to perform the following actions from your app's website: - Customers must be able to modify or cancel their {% data variables.product.prodname_marketplace %} plans for personal and organizational accounts separately. Customers should be able to perform the following actions from your app's website: - Customers should be able to modify or cancel their {% data variables.product.prodname_marketplace %} plans for personal and organizational accounts separately. {% data reusables.marketplace.marketplace-billing-ui-requirements %} ### Billing services for upgrades, downgrades, and cancellations Follow these guidelines for upgrades, downgrades, and cancellations to maintain a clear and consistent billing process. For more detailed instructions about the {% data variables.product.prodname_marketplace %} purchase events, see "[Billing flows](/marketplace/integrating-with-the-github-marketplace-api/#billing-flows)." Follow these guidelines for upgrades, downgrades, and cancellations to maintain a clear and consistent billing process. For more detailed instructions about the {% data variables.product.prodname_marketplace %} purchase events, see "[Using the {% data variables.product.prodname_marketplace %} API in your app](/developers/github-marketplace/using-the-github-marketplace-api-in-your-app)." You can use the `marketplace_purchase` webhook's `effective_date` key to determine when a plan change will occur and periodically synchronize the [List accounts for a plan](/rest/reference/apps#list-accounts-for-a-plan). @@ -33,7 +33,7 @@ When a customer upgrades their pricing plan or changes their billing cycle from {% data reusables.marketplace.marketplace-failed-purchase-event %} For information about building upgrade and downgrade workflows into your app, see "[Upgrading and downgrading plans](/marketplace/integrating-with-the-github-marketplace-api/upgrading-and-downgrading-plans/)." For information about building upgrade and downgrade workflows into your app, see "[Handling plan changes](/developers/github-marketplace/handling-plan-changes)." #### Downgrades and cancellations @@ -45,4 +45,4 @@ When a customer cancels a plan, you must: {% data reusables.marketplace.cancellation-clarification %} - Enable them to upgrade the plan through GitHub if they would like to continue the plan at a later time. For information about building cancellation workflows into your app, see "[Cancelling plans](/marketplace/integrating-with-the-github-marketplace-api/cancelling-plans/)." For information about building cancellation workflows into your app, see "[Handling plan cancellations](/developers/github-marketplace/handling-plan-cancellations)." 20 ...nt/developers/github-marketplace/customer-experience-best-practices-for-apps.md @@ -0,0 +1,20 @@ --- title: Customer experience best practices for apps intro: 'Guidelines for creating an app that will be easy to use and understand.' shortTitle: Customer experience best practice versions: free-pro-team: '*' --- If you follow these best practices it will help you to provide a good customer experience. ### Customer communication - Marketing materials for the app should accurately represent the app's behavior. - Apps should include links to user-facing documentation that describe how to set up and use the app. - Customers should be able to see what type of plan they have in the billing, profile, or account settings section of the app. - Customers should be able to install and use your app on both a personal account and an organization account. They should be able to view and manage the app on those accounts separately. ### Plan management {% data reusables.marketplace.marketplace-billing-ui-requirements %} 4 content/developers/github-marketplace/drafting-a-listing-for-your-app.md @@ -59,8 +59,8 @@ Once you've created a {% data variables.product.prodname_marketplace %} draft li ### Submitting your app Once you've completed your {% data variables.product.prodname_marketplace %} listing, you can submit your listing for review from the **Overview** page. You'll need to read and accept the "[{% data variables.product.prodname_marketplace %} Developer Agreement](/articles/github-marketplace-developer-agreement/)," and then you can click **Submit for review**. After you submit your app for review, the {% data variables.product.prodname_marketplace %} onboarding team will contact you with additional information about the onboarding process. You can learn more about the onboarding and security review process in "[Getting started with {% data variables.product.prodname_marketplace %}](/marketplace/getting-started/)." Once you've completed your {% data variables.product.prodname_marketplace %} listing, you can submit your listing for review from the **Overview** page. You'll need to read and accept the "[{% data variables.product.prodname_marketplace %} Developer Agreement](/articles/github-marketplace-developer-agreement/)," and then you can click **Submit for review**. After you submit your app for review, an onboarding expert will contact you with additional information about the onboarding process. You can learn more about the onboarding and security review process in "[Getting started with {% data variables.product.prodname_marketplace %}](/marketplace/getting-started/)." ### Removing a {% data variables.product.prodname_marketplace %} listing If you no longer want to list your app in {% data variables.product.prodname_marketplace %}, contact [marketplace@github.com](mailto:marketplace@github.com) to remove your listing. If you no longer want to list your app in {% data variables.product.prodname_marketplace %}, contact {% data variables.contact.contact_support %} to remove your listing. 2 content/developers/github-marketplace/handling-new-purchases-and-free-trials.md @@ -28,7 +28,7 @@ GitHub then sends the [`marketplace_purchase`](/webhooks/event-payloads/#marketp Read the `effective_date` and `marketplace_purchase` object from the `marketplace_purchase` webhook to determine which plan the customer purchased, when the billing cycle starts, and when the next billing cycle begins. If your app offers a free trial, read the `marketplace_purchase[on_free_trial]` attribute from the webhook. If the value is `true`, your app will need to track the free trial start date (`effective_date`) and the date the free trial ends (`free_trial_ends_on`). Use the `free_trial_ends_on` date to display the remaining days left in a free trial in your app's UI. You can do this in either a banner or in your [billing UI](/marketplace/selling-your-app/billing-customers-in-github-marketplace/#providing-billing-services-in-your-apps-ui). To learn how to handle cancellations before a free trial ends, see "[Cancelling plans](/marketplace/integrating-with-the-github-marketplace-api/cancelling-plans/)." See "[Upgrading and downgrading plans](/marketplace/integrating-with-the-github-marketplace-api/upgrading-and-downgrading-plans/)" to find out how to transition a free trial to a paid plan when a free trial expires. If your app offers a free trial, read the `marketplace_purchase[on_free_trial]` attribute from the webhook. If the value is `true`, your app will need to track the free trial start date (`effective_date`) and the date the free trial ends (`free_trial_ends_on`). Use the `free_trial_ends_on` date to display the remaining days left in a free trial in your app's UI. You can do this in either a banner or in your [billing UI](/marketplace/selling-your-app/billing-customers-in-github-marketplace/#providing-billing-services-in-your-apps-ui). To learn how to handle cancellations before a free trial ends, see "[Handling plan cancellations](/developers/github-marketplace/handling-plan-cancellations)." See "[Handling plan changes](/developers/github-marketplace/handling-plan-changes)" to find out how to transition a free trial to a paid plan when a free trial expires. See "[{% data variables.product.prodname_marketplace %} webhook events](/marketplace/integrating-with-the-github-marketplace-api/github-marketplace-webhook-events/)" for an example of the `marketplace_purchase` event payload. 6 content/developers/github-marketplace/index.md @@ -11,8 +11,10 @@ versions: {% topic_link_in_list /creating-apps-for-github-marketplace %} {% link_in_list /about-github-marketplace %} {% link_in_list /about-verified-creators %} {% link_in_list /requirements-for-listing-an-app %} {% link_in_list /security-review-process-for-submitted-apps %} {% link_in_list /security-best-practices-for-apps %} {% link_in_list /customer-experience-best-practices-for-apps %} {% link_in_list /viewing-metrics-for-your-listing %} {% link_in_list /viewing-transactions-for-your-listing %} {% topic_link_in_list /using-the-github-marketplace-api-in-your-app %} @@ -27,7 +29,7 @@ versions: {% link_in_list /writing-a-listing-description-for-your-app %} {% link_in_list /setting-pricing-plans-for-your-listing %} {% link_in_list /configuring-a-webhook-to-notify-you-of-plan-changes %} {% link_in_list /submitting-your-listing-for-review %} {% link_in_list /submitting-your-listing-for-publication %} {% topic_link_in_list /selling-your-app-on-github-marketplace %} {% link_in_list /pricing-plans-for-github-marketplace-apps %} {% link_in_list /billing-customers %} 32 content/developers/github-marketplace/pricing-plans-for-github-marketplace-apps.md @@ -10,35 +10,45 @@ versions: {% data variables.product.prodname_marketplace %} pricing plans can be free, flat rate, or per-unit, and GitHub lists the price in US dollars. Customers purchase your app using a payment method attached to their {% data variables.product.product_name %} account, without having to leave GitHub.com. You don't have to write code to perform billing transactions, but you will have to handle [billing flows](/marketplace/integrating-with-the-github-marketplace-api/#billing-flows) for purchase events. {% data variables.product.prodname_marketplace %} pricing plans can be free, flat rate, or per-unit. Prices are set, displayed, and processed in US dollars. Paid plans are restricted to verified listings. Customers purchase your app using a payment method attached to their {% data variables.product.product_name %} account, without having to leave {% data variables.product.prodname_dotcom_the_website %}. You don't have to write code to perform billing transactions, but you will have to handle events from the {% data variables.product.prodname_marketplace %} API. For more information, see "[Using the {% data variables.product.prodname_marketplace %} API in your app](/developers/github-marketplace/using-the-github-marketplace-api-in-your-app)." If the app you're listing on {% data variables.product.prodname_marketplace %} has multiple plan options, you can set up corresponding pricing plans. For example, if your app has two plan options, an open source plan and a pro plan, you can set up a free pricing plan for your open source plan and a flat pricing plan for your pro plan. Each {% data variables.product.prodname_marketplace %} listing must have an annual and a monthly price for every plan that's listed. For more information on how to create a pricing plan, see "[Setting a {% data variables.product.prodname_marketplace %} listing's pricing plan](/marketplace/listing-on-github-marketplace/setting-a-github-marketplace-listing-s-pricing-plan/)." {% note %} {% data reusables.marketplace.free-plan-note %} **Note:** If you're listing an app on {% data variables.product.prodname_marketplace %}, you can't list your app with a free pricing plan if you offer a paid service outside of {% data variables.product.prodname_marketplace %}. ### Types of pricing plans {% endnote %} #### Free pricing plans ### Types of pricing plans {% data reusables.marketplace.free-apps-encouraged %} Free plans are completely free for users. If you set up a free pricing plan, you cannot charge users that choose the free pricing plan for the use of your app. You can create both free and paid plans for your listing. All apps need to handle events for new purchases and cancellations. Apps that only have free plans do not need to handle events for free trials, upgrades, and downgrades. For more information, see: "[Using the {% data variables.product.prodname_marketplace %} API in your app](/developers/github-marketplace/using-the-github-marketplace-api-in-your-app)." If you add a paid plan to an app that you've already listed in {% data variables.product.prodname_marketplace %} as a free service, you'll need to request verification for the app and go through financial onboarding. #### Paid pricing plans **Free pricing plans** are completely free for users. If you set up a free pricing plan, you cannot charge users that choose the free pricing plan for the use of your app. You can create both free and paid plans for your listing. Unverified free apps do not need to implement any billing flows. Free apps that are verified by Github need to implement billing flows for new purchases and cancellations, but do not need to implement billing flows for free trials, upgrades, and downgrades. If you add a paid plan to an app that you've already listed in {% data variables.product.prodname_marketplace %} as a free service, you'll need to resubmit the app for review. There are two types of paid pricing plan: **Flat rate pricing plans** charge a set fee on a monthly and yearly basis. - Flat rate pricing plans charge a set fee on a monthly and yearly basis. **Per-unit pricing plans** charge a set fee on either a monthly or yearly basis for a unit that you specify. A "unit" can be anything you'd like (for example, a user, seat, or person). - Per-unit pricing plans charge a set fee on either a monthly or yearly basis for a unit that you specify. A "unit" can be anything you'd like (for example, a user, seat, or person). **Marketplace free trials** provide 14-day free trials of OAuth or GitHub Apps to customers. When you [set up a Marketplace pricing plan](/marketplace/listing-on-github-marketplace/setting-a-github-marketplace-listing-s-pricing-plan/), you can select the option to provide a free trial for flat-rate or per-unit pricing plans. You may also want to offer free trials. These provide free, 14-day trials of OAuth or GitHub Apps to customers. When you set up a Marketplace pricing plan, you can select the option to provide a free trial for flat-rate or per-unit pricing plans. ### Free trials Customers can start a free trial for any available paid plan on a Marketplace listing, but will not be able to create more than one free trial for a Marketplace product. Customers can start a free trial for any paid plan on a Marketplace listing that includes free trials. However, customers cannot create more than one free trial per marketplace product. Free trials have a fixed length of 14 days. Customers are notified 4 days before the end of their trial period (on day 11 of the free trial) that their plan will be upgraded. At the end of a free trial, customers will be auto-enrolled into the plan they are trialing if they do not cancel. See "[New purchases and free trials](/marketplace/integrating-with-the-github-marketplace-api/handling-new-purchases-and-free-trials/)" for details on how to handle free trials in your app. For more information, see: "[Handling new purchases and free trials](/developers/github-marketplace/integrating-with-the-github-marketplace-api/handling-new-purchases-and-free-trials/)." {% note %} 61 content/developers/github-marketplace/requirements-for-listing-an-app.md @@ -1,6 +1,6 @@ --- title: Requirements for listing an app intro: 'Apps on {% data variables.product.prodname_marketplace %} must meet the requirements outlined on this page before our {% data variables.product.prodname_marketplace %} onboarding specialists will approve the listing.' intro: 'Apps on {% data variables.product.prodname_marketplace %} must meet the requirements outlined on this page before the listing can be published.' redirect_from: - /apps/adding-integrations/listing-apps-on-github-marketplace/requirements-for-listing-an-app-on-github-marketplace/ - /apps/marketplace/listing-apps-on-github-marketplace/requirements-for-listing-an-app-on-github-marketplace/ @@ -12,49 +12,62 @@ versions: free-pro-team: '*' --- <!--UI-LINK: Displayed as a link on the https://github.com/marketplace/new page.--> The requirements for listing an app on {% data variables.product.prodname_marketplace %} vary according to whether you want to offer a free or a paid app. Before you submit your app for review, you must read and accept the terms of the "[{% data variables.product.prodname_marketplace %} Developer Agreement](/articles/github-marketplace-developer-agreement/)." You'll accept the terms within your [draft listing](/marketplace/listing-on-github-marketplace/creating-a-draft-github-marketplace-listing/) on {% data variables.product.product_name %}. Once you've submitted your app, one of the {% data variables.product.prodname_marketplace %} onboarding specialists will reach out to you with more information about the onboarding process, and review your app to ensure it meets these requirements: ### Requirements for all {% data variables.product.prodname_marketplace %} listings ### User experience All listings on {% data variables.product.prodname_marketplace %} should be for tools that provide value to the {% data variables.product.product_name %} community. When you submit your listing for publication, you must read and accept the terms of the "[{% data variables.product.prodname_marketplace %} Developer Agreement](/articles/github-marketplace-developer-agreement/)." - {% data variables.product.prodname_github_app %}s should have a minimum of 100 installations. - {% data variables.product.prodname_oauth_app %}s should have a minimum of 200 users. #### User experience requirements for all apps All listings should meet the following requirements, regardless of whether they are for a free or paid app. - Listings must not actively persuade users away from {% data variables.product.product_name %}. - Listings must include valid contact information for the publisher. - Listings must have a relevant description of the application. - Listings must specify a pricing plan. - Apps must provide value to customers and integrate with the platform in some way beyond authentication. - Apps must be publicly available in {% data variables.product.prodname_marketplace %} and cannot be in beta or available by invite only. - Apps cannot actively persuade users away from {% data variables.product.product_name %}. - Marketing materials for the app must accurately represent the app's behavior. - Apps must include links to user-facing documentation that describe how to set up and use the app. - When a customer purchases an app and GitHub redirects them to the app's installation URL, the app must begin the OAuth flow immediately. For details, see "[Handling new purchases and free trials](/marketplace/integrating-with-the-github-marketplace-api/handling-new-purchases-and-free-trials/#step-3-authorization)." - Apps must have webhook events set up to notify the publisher of any plan changes or cancellations using the {% data variables.product.prodname_marketplace %} API. For more information, see "[Using the {% data variables.product.prodname_marketplace %} API in your app](/developers/github-marketplace/using-the-github-marketplace-api-in-your-app)." - Customers must be able to install your app and select repositories on both a personal and organization account. They should be able to view and manage those accounts separately. For more information on providing a good customer experience, see "[Customer experience best practices for apps](/developers/github-marketplace/customer-experience-best-practices-for-apps)." ### Brand and listing #### Brand and listing requirements for all apps - Apps that use GitHub logos must follow the "[{% data variables.product.product_name %} Logos and Usage](https://github.com/logos)" guidelines. - Apps that use GitHub logos must follow the {% data variables.product.company_short %} guidelines. For more information, see "[{% data variables.product.company_short %} Logos and Usage](https://github.com/logos)." - Apps must have a logo, feature card, and screenshots images that meet the recommendations provided in "[Writing {% data variables.product.prodname_marketplace %} listing descriptions](/marketplace/listing-on-github-marketplace/writing-github-marketplace-listing-descriptions/)." - Listings must include descriptions that are well written and free of grammatical errors. For guidance in writing your listing, see "[Writing {% data variables.product.prodname_marketplace %} listing descriptions](/marketplace/listing-on-github-marketplace/writing-github-marketplace-listing-descriptions/)." ### Security To protect your customers, we recommend that you also follow security best practices. For more information, see "[Security best practices for apps](/developers/github-marketplace/security-best-practices-for-apps)." ### Considerations for free apps Apps will go through a security review before being listed on {% data variables.product.prodname_marketplace %}. A successful review will meet the requirements and follow the security best practices listed in "[Security review process](/marketplace/getting-started/security-review-process/)." For information on the review process, contact [marketplace@github.com](mailto:marketplace@github.com). {% data reusables.marketplace.free-apps-encouraged %} ### Requirements for paid apps In addition to the requirements for all apps above, each app that you offer as a paid service on {% data variables.product.prodname_marketplace %} must also meet the following requirements: - {% data variables.product.prodname_github_app %}s should have a minimum of 100 installations. - {% data variables.product.prodname_oauth_app %}s should have a minimum of 200 users. - All paid apps must handle {% data variables.product.prodname_marketplace %} purchase events for new purchases, upgrades, downgrades, cancellations, and free trials. For more information, see "[Billing requirements for paid apps](#billing-requirements-for-paid-apps)" below. - Publishing organizations must have a verified domain and must enable two-factor authentication. For more information, see "[Requiring two-factor authentication in your organization](/github/setting-up-and-managing-organizations-and-teams/requiring-two-factor-authentication-in-your-organization.") ### Billing flows When you are ready to publish the app on {% data variables.product.prodname_marketplace %} you must request verification for the listing. Your app must integrate [billing flows](/marketplace/integrating-with-the-github-marketplace-api/#billing-flows) using the [{% data variables.product.prodname_marketplace %} webhook event](/marketplace/integrating-with-the-github-marketplace-api/github-marketplace-webhook-events/). {% note %} #### Free apps The verification process is open to organizations. {% data reusables.marketplace.app-transfer-to-org-for-verification %} For information on how to do this, see: "[Submitting your listing for publication](/developers/github-marketplace/submitting-your-listing-for-publication#transferring-an-app-to-an-organization-before-you-submit)." {% data reusables.marketplace.free-apps-encouraged %} If you are listing a free app, you'll need to meet these requirements: {% endnote %} - Customers must be able to see that they have a free plan in the billing, profile, or account settings section of the app. - When a customer cancels your app, you must follow the flow for [cancelling plans](/marketplace/integrating-with-the-github-marketplace-api/cancelling-plans/). ### Billing requirements for paid apps #### Paid apps Your app does not need to handle payments but does need to use {% data variables.product.prodname_marketplace %} purchase events to manage new purchases, upgrades, downgrades, cancellations, and free trials. For information about how integrate these events into your app, see "[Using the {% data variables.product.prodname_marketplace %} API in your app](/developers/github-marketplace/using-the-github-marketplace-api-in-your-app)." To offer your app as a paid service, you'll need to meet these requirements to list your app on {% data variables.product.prodname_marketplace %}: Using GitHub's billing API allows customers to purchase an app without leaving GitHub and to pay for the service with the payment method already attached to their {% data variables.product.product_name %} account. - To sell your app in {% data variables.product.prodname_marketplace %}, it must use GitHub's billing system. Your app does not need to handle payments but does need to use "[{% data variables.product.prodname_marketplace %} purchase events](/marketplace/integrating-with-the-github-marketplace-api/github-marketplace-webhook-events/)" to manage new purchases, upgrades, downgrades, cancellations, and free trials. See "[Billing flows](/marketplace/integrating-with-the-github-marketplace-api/#billing-flows)" to learn about how to integrate these events into your app. Using GitHub's billing system allows customers to purchase an app without leaving GitHub and pay for the service with the payment method already attached to their {% data variables.product.product_name %} account. - Apps must support both monthly and annual billing for paid subscriptions purchases. - Listings may offer any combination of free and paid plans. Free plans are optional but encouraged. For more information, see "[Setting a {% data variables.product.prodname_marketplace %} listing's pricing plan](/marketplace/listing-on-github-marketplace/setting-a-github-marketplace-listing-s-pricing-plan/)." {% data reusables.marketplace.marketplace-billing-ui-requirements %} 60 content/developers/github-marketplace/security-best-practices-for-apps.md @@ -0,0 +1,60 @@ --- title: Security best practices for apps intro: 'Guidelines for preparing a secure app to share on {% data variables.product.prodname_marketplace %}.' redirect_from: - /apps/marketplace/getting-started/security-review-process/ - /marketplace/getting-started/security-review-process - /developers/github-marketplace/security-review-process-for-submitted-apps shortTitle: Security best practice versions: free-pro-team: '*' --- If you follow these best practices it will help you to provide a secure user experience. ### Authorization, authentication, and access control We recommend creating a GitHub App rather than an OAuth App. {% data reusables.marketplace.github_apps_preferred %}. See "[Differences between GitHub Apps and OAuth Apps](/apps/differences-between-apps/)" for more details. - Apps should use the principle of least privilege and should only request the OAuth scopes and GitHub App permissions that the app needs to perform its intended functionality. For more information, see [Principle of least privilege](https://en.wikipedia.org/wiki/Principle_of_least_privilege) in Wikipedia. - Apps should provide customers with a way to delete their account, without having to email or call a support person. - Apps should not share tokens between different implementations of the app. For example, a desktop app should have a separate token from a web-based app. Individual tokens allow each app to request the access needed for GitHub resources separately. - Design your app with different user roles, depending on the functionality needed by each type of user. For example, a standard user should not have access to admin functionality, and billing managers might not need push access to repository code. - Apps should not share service accounts such as email or database services to manage your SaaS service. - All services used in your app should have unique login and password credentials. - Admin privilege access to the production hosting infrastructure should only be given to engineers and employees with administrative duties. - Apps should not use personal access tokens to authenticate and should authenticate as an [OAuth App](/apps/about-apps/#about-oauth-apps) or a [GitHub App](/apps/about-apps/#about-github-apps): - OAuth Apps should authenticate using an [OAuth token](/apps/building-oauth-apps/authorizing-oauth-apps/). - GitHub Apps should authenticate using either a [JSON Web Token (JWT)](/apps/building-github-apps/authenticating-with-github-apps/#authenticating-as-a-github-app), [OAuth token](/apps/building-github-apps/identifying-and-authorizing-users-for-github-apps/), or [installation access token](/apps/building-github-apps/authenticating-with-github-apps/#authenticating-as-an-installation). ### Data protection - Apps should encrypt data transferred over the public internet using HTTPS, with a valid TLS certificate, or SSH for Git. - Apps should store client ID and client secret keys securely. We recommend storing them as [environmental variables](http://en.wikipedia.org/wiki/Environment_variable#Getting_and_setting_environment_variables). - Apps should delete all GitHub user data within 30 days of receiving a request from the user, or within 30 days of the end of the user's legal relationship with GitHub. - Apps should not require the user to provide their GitHub password. - Apps should encrypt tokens, client IDs, and client secrets. ### Logging and monitoring Apps should have logging and monitoring capabilities. App logs should be retained for at least 30 days and archived for at least one year. A security log should include: - Authentication and authorization events - Service configuration changes - Object reads and writes - All user and group permission changes - Elevation of role to admin - Consistent timestamping for each event - Source users, IP addresses, and/or hostnames for all logged actions ### Incident response workflow To provide a secure experience for users, you should have a clear incident response plan in place before listing your app. We recommend having a security and operations incident response team in your company rather than using a third-party vendor. You should have the capability to notify {% data variables.product.product_name %} within 24 hours of a confirmed incident. For an example of an incident response workflow, see the "Data Breach Response Policy" on the [SANS Institute website](https://www.sans.org/information-security-policy/). A short document with clear steps to take in the event of an incident is more valuable than a lengthy policy template. ### Vulnerability management and patching workflow You should conduct regular vulnerability scans of production infrastructure. You should triage the results of vulnerability scans and define a period of time in which you agree to remediate the vulnerability. If you are not ready to set up a full vulnerability management program, it's useful to start by creating a patching process. For guidance in creating a patch management policy, see this TechRepublic article "[Establish a patch management policy](https://www.techrepublic.com/blog/it-security/establish-a-patch-management-policy-87756/)." 94 ...ent/developers/github-marketplace/security-review-process-for-submitted-apps.md This file was deleted. 53 content/developers/github-marketplace/setting-pricing-plans-for-your-listing.md @@ -1,6 +1,6 @@ --- title: Setting pricing plans for your listing intro: 'When [listing your app on {% data variables.product.prodname_marketplace %}](/marketplace/listing-on-github-marketplace/), you can choose to provide your app as a free service or sell your app. If you plan to sell your app, you can create different pricing plans for different feature tiers.' intro: 'When you list your app on {% data variables.product.prodname_marketplace %}, you can choose to provide your app as a free service or sell your app. If you plan to sell your app, you can create different pricing plans for different feature tiers.' redirect_from: - /apps/adding-integrations/managing-pricing-and-payments-for-a-github-marketplace-listing/setting-a-github-marketplace-listing-s-pricing-plan/ - /apps/marketplace/managing-pricing-and-payments-for-a-github-marketplace-listing/setting-a-github-marketplace-listing-s-pricing-plan/ @@ -17,57 +17,52 @@ versions: free-pro-team: '*' --- ### About setting pricing plans If you want to sell an app on {% data variables.product.prodname_marketplace %}, you need to request verification when you publish the listing for your app. During the verification process, an onboarding expert checks the organization's identity and security settings. The onboarding expert will also take the organization through financial onboarding. For more information, see: "[Requirements for listing an app on {% data variables.product.prodname_marketplace %}](/marketplace/getting-started/requirements-for-listing-an-app-on-github-marketplace/)." ### Creating pricing plans To learn about the types of pricing plans that {% data variables.product.prodname_marketplace %} offers, see "[{% data variables.product.prodname_marketplace %} Pricing Plans](/marketplace/selling-your-app/github-marketplace-pricing-plans/)." You'll also find helpful billing guidelines in "[Selling your app](/marketplace/selling-your-app/)." Pricing plans can be in the draft or published state. If you haven't submitted your {% data variables.product.prodname_marketplace %} listing for approval, a published listing will function the same way as draft listings until your app is approved and listed on {% data variables.product.prodname_marketplace %}. Draft listings allow you to create and save new pricing plans without making them available on your {% data variables.product.prodname_marketplace %} listing page. Once you publish the pricing plan, it's available for customers to purchase immediately. You can publish up to 10 pricing plans. {% data reusables.marketplace.app-transfer-to-org-for-verification %} For information on how to do this, see: "[Submitting your listing for publication](/developers/github-marketplace/submitting-your-listing-for-publication#transferring-an-app-to-an-organization-before-you-submit)." To create a pricing plan for your {% data variables.product.prodname_marketplace %} listing, click **Plans and pricing** in the left sidebar of your [{% data variables.product.prodname_marketplace %} listing page](https://github.com/marketplace/manage). If you haven't created a {% data variables.product.prodname_marketplace %} listing yet, read "[Creating a draft {% data variables.product.prodname_marketplace %} listing](/marketplace/listing-on-github-marketplace/creating-a-draft-github-marketplace-listing/)" to learn how. When you click **New draft plan**, you'll see a form that allows you to customize your pricing plan. You'll need to configure the following fields to create a pricing plan: {% data variables.product.prodname_marketplace %} offers several different types of pricing plan. For detailed information, see "[Pricing plans for {% data variables.product.prodname_marketplace %}](/developers/github-marketplace/pricing-plans-for-github-marketplace-apps)." #### Plan name ### About saving pricing plans Your pricing plan's name will appear on your {% data variables.product.prodname_marketplace %} app's landing page. You can customize the name of your pricing plan to align to the plan's resources, the size of the company that will use the plan, or anything you'd like. You can save pricing plans in a draft or published state. If you haven't submitted your {% data variables.product.prodname_marketplace %} listing for approval, a published plan will function in the same way as a draft plan until your listing is approved and shown on {% data variables.product.prodname_marketplace %}. Draft plans allow you to create and save new pricing plans without making them available on your {% data variables.product.prodname_marketplace %} listing page. Once you publish a pricing plan on a published listing, it's available for customers to purchase immediately. You can publish up to 10 pricing plans. #### Pricing models For guidelines on billing customers, see "[Billing customers](/developers/github-marketplace/billing-customers)." ##### Free plans {% data reusables.marketplace.free-apps-encouraged %} A free plan still requires you to handle [new purchase](/marketplace/integrating-with-the-github-marketplace-api/handling-new-purchases-and-free-trials/) and [cancellation](/marketplace/integrating-with-the-github-marketplace-api/cancelling-plans/) billing flows. See "[Billing flows](/marketplace/integrating-with-the-github-marketplace-api/#billing-flows)" for more details. ##### Flat-rate plans ### Creating pricing plans Flat-rate pricing plans allow you to offer your service to customers for a flat-rate fee. {% data reusables.marketplace.marketplace-pricing-free-trials %} To create a pricing plan for your {% data variables.product.prodname_marketplace %} listing, click **Plans and pricing** in the left sidebar of your [{% data variables.product.prodname_marketplace %} listing page](https://github.com/marketplace/manage). For more information, see "[Creating a draft {% data variables.product.prodname_marketplace %} listing](/marketplace/listing-on-github-marketplace/creating-a-draft-github-marketplace-listing/)." You must set a price for both monthly and yearly subscriptions in U.S. Dollars for flat-rate plans. When you click **New draft plan**, you'll see a form that allows you to customize your pricing plan. You'll need to configure the following fields to create a pricing plan: ##### Per-unit plans - **Plan name** - Your pricing plan's name will appear on your {% data variables.product.prodname_marketplace %} app's landing page. You can customize the name of your pricing plan to align with the plan's resources, the size of the company that will use the plan, or anything you'd like. Per-unit pricing allows you to offer your app in units. For example, a unit can be a person, seat, or user. You'll need to provide a name for the unit and set a price for both monthly and yearly subscriptions, in U.S. Dollars. - **Pricing models** - There are three types of pricing plan: free, flat-rate, and per-unit. All plans require you to process new purchase and cancellation events from the marketplace API. In addition, for paid plans: #### Available for - You must set a price for both monthly and yearly subscriptions in US dollars. - Your app must process plan change events. - You must request verification to publish a listing with a paid plan. - {% data reusables.marketplace.marketplace-pricing-free-trials %} {% data variables.product.prodname_marketplace %} pricing plans can apply to **Personal and organization accounts**, **Personal accounts only**, or **Organization accounts only**. For example, if your pricing plan is per-unit and provides multiple seats, you would select **Organization accounts only** because there is no way to assign seats to people in an organization from a personal account. For detailed information, see "[Pricing plans for {% data variables.product.prodname_marketplace %} apps](/developers/github-marketplace/pricing-plans-for-github-marketplace-apps)" and "[Using the {% data variables.product.prodname_marketplace %} API in your app](/developers/github-marketplace/using-the-github-marketplace-api-in-your-app)." #### Short description - **Available for** - {% data variables.product.prodname_marketplace %} pricing plans can apply to **Personal and organization accounts**, **Personal accounts only**, or **Organization accounts only**. For example, if your pricing plan is per-unit and provides multiple seats, you would select **Organization accounts only** because there is no way to assign seats to people in an organization from a personal account. Write a brief summary of the details of the pricing plan. The description might include the type of customer the plan is intended for or the resources the plan includes. - **Short description** - Write a brief summary of the details of the pricing plan. The description might include the type of customer the plan is intended for or the resources the plan includes. #### Bullets - **Bullets** - You can write up to four bullets that include more details about your pricing plan. The bullets might include the use cases of your app or list more detailed information about the resources or features included in the plan. You can write up to four bullets that include more details about your pricing plan. The bullets might include the use cases of your app or list more detailed information about the resources or features included in the plan. {% data reusables.marketplace.free-plan-note %} ### Changing a {% data variables.product.prodname_marketplace %} listing's pricing plan If a pricing plan for your {% data variables.product.prodname_marketplace %} plan is no longer needed or if you need to adjust pricing details, you can remove it. If a pricing plan for your {% data variables.product.prodname_marketplace %} listing is no longer needed, or if you need to adjust pricing details, you can remove it.  Once you publish a pricing plan for an app already listed in the {% data variables.product.prodname_marketplace %}, you can't make changes to the plan. Instead, you'll need to remove the pricing plan. Customers who already purchased the removed pricing plan will continue to use it until they opt out and move onto a new pricing plan. For more on pricing plans, see "[{% data variables.product.prodname_marketplace %} pricing plans](/marketplace/selling-your-app/github-marketplace-pricing-plans/)." Once you publish a pricing plan for an app that is already listed in {% data variables.product.prodname_marketplace %}, you can't make changes to the plan. Instead, you'll need to remove the pricing plan and create a new plan. Customers who already purchased the removed pricing plan will continue to use it until they opt out and move onto a new pricing plan. For more on pricing plans, see "[{% data variables.product.prodname_marketplace %} pricing plans](/marketplace/selling-your-app/github-marketplace-pricing-plans/)." Once you remove a pricing plan, users won't be able to purchase your app using that plan. Existing users on the removed pricing plan will continue to stay on the plan until they cancel their plan subscription. 37 content/developers/github-marketplace/submitting-your-listing-for-publication.md @@ -0,0 +1,37 @@ --- title: Submitting your listing for publication intro: 'You can submit your listing for the {% data variables.product.prodname_dotcom %} community to use.' redirect_from: - /marketplace/listing-on-github-marketplace/submitting-your-listing-for-review - /developers/github-marketplace/submitting-your-listing-for-review versions: free-pro-team: '*' --- Once you've completed the listing for your app, you'll see two buttons that allow you to request publication of the listing with or without verification. The **Request** button for "Publish without verification" is disabled if you have published any paid pricing plans in the listing.  {% data reusables.marketplace.launch-with-free %} After you submit your listing for review, an onboarding expert will reach out to you with additional information. For an overview of the process for creating and submitting a listing, see "[About {% data variables.product.prodname_marketplace %}](/developers/github-marketplace/about-github-marketplace#publishing-an-app-to-github-marketplace)." ### Prerequisites for publishing with verification Before you request verification of your listing, you'll need to integrate the {% data variables.product.prodname_marketplace %} billing flows and webhook into your app. For more information, see "[Using the {% data variables.product.prodname_marketplace %} API in your app](/developers/github-marketplace/using-the-github-marketplace-api-in-your-app)." If you've met the requirements for listing and you've integrated with the {% data variables.product.prodname_marketplace %} API, go ahead and submit your listing. For more information, see "[Requirements for listing an app](/developers/github-marketplace/requirements-for-listing-an-app)." {% data reusables.marketplace.app-transfer-to-org-for-verification %} For information on how to do this, see: "[Transferring an app to an organization before you submit](#transferring-an-app-to-an-organization-before-you-submit)" below. ### Transferring an app to an organization before you submit You cannot sell an app that's owned by a user account. You need to transfer the app to an organization that is already a verified creator, or that can request verification for a listing for the app. For details, see: 1. "[Creating an organization from scratch](/github/setting-up-and-managing-organizations-and-teams/creating-a-new-organization-from-scratch)" 1. "[Transferring ownership of a GitHub App](/developers/apps/transferring-ownership-of-a-github-app)" or "[Transferring ownership of an OAuth App](/developers/apps/transferring-ownership-of-an-oauth-app)" 22 content/developers/github-marketplace/submitting-your-listing-for-review.md This file was deleted. 4 content/developers/github-marketplace/testing-your-app.md @@ -1,6 +1,6 @@ --- title: Testing your app intro: 'GitHub recommends testing your app with APIs and webhooks before submitting your listing to {% data variables.product.prodname_marketplace %} so you can provide an ideal experience for customers. Before the {% data variables.product.prodname_marketplace %} onboarding team approves your app, it must adequately handle the [billing flows](/marketplace/integrating-with-the-github-marketplace-api/#billing-flows).' intro: 'GitHub recommends testing your app with APIs and webhooks before submitting your listing to {% data variables.product.prodname_marketplace %} so you can provide an ideal experience for customers. Before an onboarding expert approves your app, it must adequately handle the billing flows.' redirect_from: - /apps/marketplace/testing-apps-apis-and-webhooks/ - /apps/marketplace/integrating-with-the-github-marketplace-api/testing-github-marketplace-apps/ @@ -13,7 +13,7 @@ versions: ### Testing apps You can use a [draft {% data variables.product.prodname_marketplace %} listing](/marketplace/listing-on-github-marketplace/creating-a-draft-github-marketplace-listing/) to simulate each of the [billing flows](/marketplace/integrating-with-the-github-marketplace-api/#billing-flows). A listing in the draft state means that it has not been submitted for approval. Any purchases you make using a draft {% data variables.product.prodname_marketplace %} listing will _not_ create real transactions, and GitHub will not charge your credit card. You can use a draft {% data variables.product.prodname_marketplace %} listing to simulate each of the billing flows. A listing in the draft state means that it has not been submitted for approval. Any purchases you make using a draft {% data variables.product.prodname_marketplace %} listing will _not_ create real transactions, and GitHub will not charge your credit card. For more information, see "[Drafting a listing for your app](/developers/github-marketplace/drafting-a-listing-for-your-app)" and "[Using the {% data variables.product.prodname_marketplace %} API in your app](/developers/github-marketplace/using-the-github-marketplace-api-in-your-app)." #### Using a development app with a draft listing to test changes 2 .../developers/github-marketplace/webhook-events-for-the-github-marketplace-api.md @@ -1,6 +1,6 @@ --- title: Webhook events for the GitHub Marketplace API intro: 'A {% data variables.product.prodname_marketplace %} app receives information about changes to a user''s plan from the Marketplace purchase event webhook. A Marketplace purchase event is triggered when a user purchases, cancels, or changes their payment plan. For details on how to respond to each of these types of events, see "[Billing flows](/marketplace/integrating-with-the-github-marketplace-api/#billing-flows)."' intro: 'A {% data variables.product.prodname_marketplace %} app receives information about changes to a user''s plan from the Marketplace purchase event webhook. A Marketplace purchase event is triggered when a user purchases, cancels, or changes their payment plan.' redirect_from: - /apps/marketplace/setting-up-github-marketplace-webhooks/about-webhook-payloads-for-a-github-marketplace-listing/ - /apps/marketplace/integrating-with-the-github-marketplace-api/github-marketplace-webhook-events/ 4 content/developers/webhooks-and-events/webhook-events-and-payloads.md @@ -445,7 +445,7 @@ Key | Type | Description #### Webhook payload object {% data reusables.webhooks.installation_properties %} {% data reusables.webhooks.app_desc %} {% data reusables.webhooks.app_always_desc %} {% data reusables.webhooks.sender_desc %} #### Webhook payload example @@ -469,7 +469,7 @@ Key | Type | Description #### Webhook payload object {% data reusables.webhooks.installation_repositories_properties %} {% data reusables.webhooks.app_desc %} {% data reusables.webhooks.app_always_desc %} {% data reusables.webhooks.sender_desc %} #### Webhook payload example 54 ...ssions/collaborating-with-your-community-using-discussions/about-discussions.md @@ -0,0 +1,54 @@ --- title: About discussions intro: Use discussions to ask and answer questions, share information, make announcements, and conduct or participate in a conversation about a project on {% data variables.product.product_name %}. versions: free-pro-team: '*' --- {% data reusables.discussions.beta %} ### About discussions With {% data variables.product.prodname_discussions %}, the community for your project can create and participate in conversations within the project's repository. Discussions empower a project's maintainers, contributors, and visitors to gather and accomplish the following goals in a central location, without third-party tools. - Share announcements and information, gather feedback, plan, and make decisions - Ask questions, discuss and answer the questions, and mark the discussions as answered - Foster an inviting atmosphere for visitors and contributors to discuss goals, development, administration, and workflows  You don't need to close a discussion like you close an issue or a pull request. If a repository administrator or project maintainer enables discussions for a repository, anyone who visits the repository can create and participate in discussions for the repository. Repository administrators and project maintainers can manage discussions and discussion categories in a repository, and pin discussions to increase the visibility of the discussion. Moderators and collaborators can mark comments as answers, lock discussions, and convert issues to discussions. For more information, see "[Repository permission levels for an organization](/github/setting-up-and-managing-organizations-and-teams/repository-permission-levels-for-an-organization)." For more information about management of discussions for your repository, see "[Managing discussions in your repository](/discussions/managing-discussions-for-your-community/managing-discussions-in-your-repository)." ### About categories and formats for discussions {% data reusables.discussions.you-can-categorize-discussions %} {% data reusables.discussions.about-categories-and-formats %} {% data reusables.discussions.repository-category-limit %} For discussions with a question/answer format, an individual comment within the discussion can be marked as the discussion's answer. {% data reusables.discussions.github-recognizes-members %} For more information, see "[Managing categories for discussions in your repository](/discussions/managing-discussions-for-your-community/managing-categories-for-discussions-in-your-repository)." ### Best practices for discussions As a community member or maintainer, start a discussion to ask a question or discuss information that affects the community. For more information, see "[Collaborating with maintainers using discussions](/discussions/collaborating-with-your-community-using-discussions/collaborating-with-maintainers-using-discussions)." Participate in a discussion to ask and answer questions, provide feedback, and engage with the project's community. For more information, see "[Participating in a discussion](/discussions/collaborating-with-your-community-using-discussions/participating-in-a-discussion)." You can spotlight discussions that contain important, useful, or exemplary conversations among members in the community. For more information, see "[Managing discussions in your repository](/discussions/managing-discussions-for-your-community/managing-discussions-in-your-repository#pinning-a-discussion)." {% data reusables.discussions.you-can-convert-an-issue %} For more information, see "[Moderating discussions in your repository](/discussions/managing-discussions-for-your-community/moderating-discussions#converting-an-issue-to-a-discussion)." ### Sharing feedback You can share your feedback about {% data variables.product.prodname_discussions %} with {% data variables.product.company_short %}. To join the conversation, see [`github/feedback`](https://github.com/github/feedback/discussions?discussions_q=category%3A%22Discussions+Feedback%22). ### Further reading - "[About writing and formatting on {% data variables.product.prodname_dotcom %}](/github/writing-on-github/about-writing-and-formatting-on-github)" - "[Searching discussions](/github/searching-for-information-on-github/searching-discussions)" - "[About notifications](/github/managing-subscriptions-and-notifications-on-github/about-notifications)" - "[Moderating comments and conversations](/github/building-a-strong-community/moderating-comments-and-conversations)" - "[Maintaining your safety on {% data variables.product.prodname_dotcom %}](/github/building-a-strong-community/maintaining-your-safety-on-github)" 50 ...community-using-discussions/collaborating-with-maintainers-using-discussions.md @@ -0,0 +1,50 @@ --- title: Collaborating with maintainers using discussions shortTitle: Collaborating with maintainers intro: You can contribute to the goals, plans, health, and community for a project on {% data variables.product.product_name %} by communicating with the maintainers of the project in a discussion. permissions: People with read permissions to a repository can start and participate in discussions in the repository. versions: free-pro-team: '*' --- {% data reusables.discussions.beta %} ### About collaboration with maintainers using discussions {% data reusables.discussions.about-discussions %} If you use or contribute to a project, you can start a discussion to make suggestions and engage with maintainers and community members about your plans, questions, ideas, and feedback. For more information, see "[About discussions](/discussions/collaborating-with-your-community-using-discussions/about-discussions)." {% data reusables.discussions.about-categories-and-formats %} Repository administrators and project maintainers can delete a discussion. For more information, see "[Managing discussions in your repository](/discussions/managing-discussions-for-your-community/managing-discussions-in-your-repository#deleting-a-discussion)." {% data reusables.discussions.github-recognizes-members %} These members appear in a list of the most helpful contributors to the project's discussions. As your project grows, you can grant higher access permissions to active members of your community. For more information, see "[Granting higher permissions to top contributors](/discussions/guides/granting-higher-permissions-to-top-contributors)"  For more information about participation in discussions, see "[Participating in a discussion](/discussions/collaborating-with-your-community-using-discussions/participating-in-a-discussion)." ### Prerequisites To collaborate with maintainers using discussions, a repository administrator or project maintainer must enable discussions for the repository. For more information, see "[Enabling or disabling discussions for a repository](/github/administering-a-repository/enabling-or-disabling-github-discussions-for-a-repository)." ### Starting a discussion {% data reusables.discussions.starting-a-discussion %} ### Filtering the list of discussions You can search for discussions and filter the list of discussions in a repository. For more information, see "[Searching discussions](/github/searching-for-information-on-github/searching-discussions)." {% data reusables.repositories.navigate-to-repo %} {% data reusables.discussions.discussions-tab %} 1. In the **Search all discussions** field, type a search query. Optionally, to the right of the search field, click a button to further filter the results.  1. In the list of discussions, click the discussion you want to view.  ### Converting an issue to a discussion {% data reusables.discussions.you-can-convert-an-issue %} For more information, see "[Moderating discussions in your repository](/discussions/managing-discussions-for-your-community/moderating-discussions#converting-an-issue-to-a-discussion#converting-an-issue-to-a-discussion)." ### Further reading - "[About writing and formatting on {% data variables.product.prodname_dotcom %}](/github/writing-on-github/about-writing-and-formatting-on-github)" - "[Maintaining your safety on {% data variables.product.prodname_dotcom %}](/github/building-a-strong-community/maintaining-your-safety-on-github)" 14 content/discussions/collaborating-with-your-community-using-discussions/index.md @@ -0,0 +1,14 @@ --- title: Collaborating with your community using discussions shortTitle: Collaborating using discussions intro: Gather and discuss your project with community members and other maintainers. versions: free-pro-team: '*' --- {% data reusables.discussions.beta %} {% link_in_list /about-discussions %} {% link_in_list /participating-in-a-discussion %} {% link_in_list /collaborating-with-maintainers-using-discussions %} 31 ...borating-with-your-community-using-discussions/participating-in-a-discussion.md @@ -0,0 +1,31 @@ --- title: Participating in a discussion intro: You can converse with the community and maintainers in a forum within the repository for a project on {% data variables.product.product_name %}. permissions: People with read permissions to a repository can participate in discussions in the repository. versions: free-pro-team: '*' --- {% data reusables.discussions.beta %} ### About participation in a discussion {% data reusables.discussions.about-discussions %} For more information, see "[About discussions](/discussions/collaborating-with-your-community-using-discussions/about-discussions)." In addition to starting or viewing a discussion, you can comment in response to the original comment from the author of the discussion. You can also create a comment thread by replying to an individual comment that another community member made within the discussion, and react to comments with emoji. For more information about reactions, see "[About conversations on {% data variables.product.prodname_dotcom %}](/github/collaborating-with-issues-and-pull-requests/about-conversations-on-github#reacting-to-ideas-in-comments)." You can block users and report disruptive content to maintain a safe and pleasant environment for yourself on {% data variables.product.product_name %}. For more information, see "[Maintaining your safety on {% data variables.product.prodname_dotcom %}](/github/building-a-strong-community/maintaining-your-safety-on-github)." ### Prerequisites Discussions must be enabled for the repository for you to participate in a discussion in the repository. For more information, see "[Enabling or disabling discussions for a repository](/github/administering-a-repository/enabling-or-disabling-github-discussions-for-a-repository)." ### Creating a discussion {% data reusables.discussions.starting-a-discussion %} ### Marking a comment as an answer Discussion authors and users with the triage role or greater for a repository can mark a comment as the answer to a discussion in the repository. {% data reusables.discussions.marking-a-comment-as-an-answer %} 49 content/discussions/guides/best-practices-for-community-conversations-on-github.md @@ -0,0 +1,49 @@ --- title: Best practices for community conversations on GitHub shortTitle: Best practices for community conversations intro: 'You can use discussions to brainstorm with your team, and eventually move the conversation to a discussion when you are ready to scope out the work.' versions: free-pro-team: '*' --- {% data reusables.discussions.beta %} ### Community conversations in {% data variables.product.prodname_discussions %} Since {% data variables.product.prodname_discussions %} is an open forum, there is an opportunity to bring non-code collaboration into a project's repository and gather diverse feedback and ideas more quickly. You can help drive a productive conversation by: - Asking pointed questions and follow-up questions to garner specific feedback - Capture a diverse experience and distill it down to main points - Open an issue to take action based on the conversation, where applicable For more information about opening an issue and cross-referencing a discussion, see "[Opening an issue from a comment](/github/managing-your-work-on-github/opening-an-issue-from-a-comment)." ### Learning about conversations on GitHub You can create and participate in discussions, issues, and pull requests, depending on the type of conversation you'd like to have. You can use {% data variables.product.prodname_discussions %} to discuss big picture ideas, brainstorm, and spike out a project's specific details before committing it to an issue, which can then be scoped. Discussions are useful for teams if: - You are in the discovery phase of a project and are still learning which director your team wants to go in - You want to collect feedback from a wider community about a project - You want to keep bug fixes, feature requests, and general conversations separate Issues are useful for discussing specific details of a project such as bug reports and planned improvements. For more information, see "[About issues](/articles/about-issues)." Pull requests allow you to comment directly on proposed changes. For more information, see "[About pull requests](/articles/about-pull-requests)" and "[Commenting on a pull request](/articles/commenting-on-a-pull-request)." {% data reusables.organizations.team-discussions-purpose %} For more information, see "[About team discussions](/articles/about-team-discussions)." ### Following contributing guidelines Before you open a discussion, check to see if the repository has contributing guidelines. The CONTRIBUTING file includes information about how the repository maintainer would like you to contribute ideas to the project. For more information, see "[Setting up your project for healthy contributions](/github/building-a-strong-community/setting-up-your-project-for-healthy-contributions)." ### Next steps To continue learning about {% data variables.product.prodname_discussions %} and quickly create a discussion for your community, see "[Quickstart for {% data variables.product.prodname_discussions %}](/discussions/quickstart)." ### Further reading - "[Setting up your project for healthy contributions](/articles/setting-up-your-project-for-healthy-contributions)" - "[Using templates to encourage useful issues and pull requests](/github/building-a-strong-community/using-templates-to-encourage-useful-issues-and-pull-requests)" - "[Moderating comments and conversations](/articles/moderating-comments-and-conversations)" - "[Writing on {% data variables.product.prodname_dotcom %}](/articles/writing-on-github)" 21 content/discussions/guides/finding-discussions-across-multiple-repositories.md @@ -0,0 +1,21 @@ --- title: Finding discussions across multiple repositories intro: 'You can easily access every discussion you''ve created or participated in across multiple repositories.' versions: free-pro-team: '*' --- {% data reusables.discussions.beta %} ### Finding discussions 1. Navigate to {% data variables.product.prodname_dotcom_the_website %}. 1. In the top-right corner of {% data variables.product.prodname_dotcom_the_website %}, click your profile photo, then click **Your enterprises**.  1. Toggle between **Created** and **Commented** to see the discussions you've created or participated in. ### Further reading - "[Searching discussions](/github/searching-for-information-on-github/searching-discussions)" - "[About discussions](/discussions/collaborating-with-your-community-using-discussions/about-discussions)" - "[Managing discussions for your community](/discussions/managing-discussions-for-your-community)" 32 content/discussions/guides/granting-higher-permissions-to-top-contributors.md @@ -0,0 +1,32 @@ --- title: Granting higher permissions to top contributors intro: 'Repository administrators can promote any community member to a moderator and maintainer.' versions: free-pro-team: '*' --- {% data reusables.discussions.beta %} ### Introduction The most helpful contributors for the past 30 days are highlighted on the {% data variables.product.prodname_discussions %} dashboard, based on how many comments were marked as answers by other community members. Helpful contributors can help drive a healthy community and moderate and guide the community space in addition to maintainers. ### Step 1: Audit your discussions top contributors {% data reusables.repositories.navigate-to-repo %} {% data reusables.discussions.discussions-tab %} 1. Compare the list of contributors with their access permissions to see who qualifies to moderate the discussion. ### Step 2: Review permission levels for discussions People with triage permissions for a repository can help moderate a project's discussions by marking comments as answers, locking discussions that are not longer useful or are damaging to the community, and converting issues to discussions when an idea is still in the early stages of development. For more information, see "[Moderating discussions](/discussions/managing-discussions-for-your-community/moderating-discussions)." For more information about repository permission levels and {% data variables.product.prodname_discussions %}, see "[Repository permissions levels for an organization](/github/setting-up-and-managing-organizations-and-teams/repository-permission-levels-for-an-organization)." ### Step 3: Change permissions levels for top contributors You can change a contributor's permission levels to give them more access to the tooling they need to moderate GitHub Discussions. To change a person's or team's permission levels, see "[Managing teams and people with access to your repository](/github/administering-a-repository/managing-teams-and-people-with-access-to-your-repository)." ### Step 4: Notify community members of elevated access When you change a collaborators permission level, they will receive a notification for the change. 29 content/discussions/guides/index.md @@ -0,0 +1,29 @@ --- title: Discussions guides shortTitle: Guides intro: 'Discover pathways to get started or learn best practices for participating or monitoring your community''s discussions.' versions: free-pro-team: '*' --- {% data reusables.discussions.beta %} ### Getting started with discussions {% link_in_list /about-discussions %} {% link_in_list /best-practices-for-community-conversations-on-github %} {% link_in_list /finding-discussions-across-multiple-repositories %} <!-- {% link_in_list /managing-notifications-for-discussions %} --> ### Administering discussions {% link_in_list /granting-higher-permissions-to-top-contributors %} <!--<!-- Commenting out what is only nice to have for discussions release {% link_in_list /updating-your-contributing-guidelines-with-discussions %} --> <!-- ### Discussions and open source projects {% link_in_list /collaborating-on-open-source-projects-in-discussions %} {% link_in_list /welcoming-contributions-to-your-communitys-discussions %} --> 55 content/discussions/index.md @@ -0,0 +1,55 @@ --- title: GitHub Discussions Documentation beta_product: true shortTitle: GitHub Discussions intro: '{% data variables.product.prodname_discussions %} is a collaborative communication forum for the community around an open source project. Community members can ask and answer questions, share updates, have open-ended conversations, and follow along on decisions affecting the community''s way of working.' introLinks: quickstart: /discussions/quickstart featuredLinks: guides: - /discussions/collaborating-with-your-community-using-discussions/about-discussions - /discussions/collaborating-with-your-community-using-discussions/participating-in-a-discussion - /discussions/managing-discussions-for-your-community/moderating-discussions gettingStarted: - /discussions/quickstart guideCards: - /discussions/collaborating-with-your-community-using-discussions/about-discussions - /discussions/collaborating-with-your-community-using-discussions/participating-in-a-discussion - /discussions/managing-discussions-for-your-community/moderating-discussions popular: - /discussions/guides/granting-higher-permissions-to-top-contributors - /discussions/guides/best-practices-for-community-conversations-on-github - /discussions/guides/finding-discussions-across-multiple-repositories - /discussions/collaborating-with-your-community-using-discussions/collaborating-with-maintainers-using-discussions - /discussions/managing-discussions-for-your-community/managing-categories-for-discussions-in-your-repository product_video: https://www.youtube-nocookie.com/embed/DbTWBP3_RbM layout: product-landing versions: free-pro-team: '*' --- <!-- {% link_with_intro /quickstart %} --> <!-- {% link_with_intro /discussions-guides %} --> <!-- {% link_with_intro /collaborating-with-your-community-using-discussions %} --> <!-- {% link_with_intro /managing-discussions-for-your-community %} --> <!-- Community examples --> {% assign discussionsCommunityExamples = site.data.variables.discussions_community_examples %} {% if discussionsCommunityExamples %} <div class="my-6 pt-6"> <h2 class="mb-2 font-mktg h1">Communities using discussions</h2> <div class="d-flex flex-wrap gutter"> {% render 'discussions-community-card' for discussionsCommunityExamples as example %} </div> {% if discussionsCommunityExamples.length > 6 %} <button class="js-filter-card-show-more btn btn-outline float-right">Show more {% octicon "arrow-right" %}</button> {% endif %} <div class="js-filter-card-no-results d-none py-4 text-center text-gray font-mktg"> <div class="mb-3">{% octicon "search" width="24" %}</div> <h3 class="text-normal">Sorry, there is no result for <strong class="js-filter-card-value"></strong></h3> <p class="my-3 f4">It looks like we don't have an example that fits your filter.<br>Try another filter or add your code example</p> <a href="https://github.com/github/docs/blob/main/data/variables/discussions_community_examples.yml">Add your community {% octicon "arrow-right" %}</a> </div> </div> {% endif %} 13 content/discussions/managing-discussions-for-your-community/index.md @@ -0,0 +1,13 @@ --- title: Managing discussions for your community shortTitle: Managing discussions intro: 'You can enable and configure discussions for your repository, and you can use tools on {% data variables.product.product_name %} to moderate conversations among community members.' versions: free-pro-team: '*' --- {% data reusables.discussions.beta %} {% link_in_list /managing-discussions-in-your-repository %} {% link_in_list /managing-categories-for-discussions-in-your-repository %} {% link_in_list /moderating-discussions %} 64 ...ns-for-your-community/managing-categories-for-discussions-in-your-repository.md @@ -0,0 +1,64 @@ --- title: Managing categories for discussions in your repository intro: You can categorize the discussions in your repository to organize conversations for your community members, and you can choose a format for each category. permissions: Repository administrators and people with write or greater access to a repository can enable discussions in the repository. versions: free-pro-team: '*' --- {% data reusables.discussions.beta %} ### About categories for discussions {% data reusables.discussions.about-discussions %} {% data reusables.discussions.about-categories-and-formats %} Each category must have a unique name and emoji pairing, and can be accompanied by a detailed description stating its purpose. Categories help maintainers organize how conversations are filed and are customizable to help distinguish categories that are Q&A or more open-ended conversations.{% data reusables.discussions.repository-category-limit %} For more information, see "[About discussions](/discussions/collaborating-with-your-community-using-discussions/about-discussions#about-categories-and-formats-for-discussions)." ### Default categories | Category | Purpose | Type | | :- | :- | :- | | #️⃣ General | Anything and everything relevant to the project | Open-ended discussion | |💡Ideas | Ideas to change or improve the project | Open-ended discussion | | 🙏 Q&A | Questions for the community to answer, with a question/answer format | Question and Answer | | 🙌 Show and tell | Creations, experiments, or tests relevant to the project | Open-ended discussion | ### Creating a category {% data reusables.repositories.navigate-to-repo %} {% data reusables.discussions.discussions-tab %} {% data reusables.discussions.edit-categories %} 1. Click **New category**.  1. Edit the emoji, title, description, and discussion format for the category. For more information about discussion formats, see "[About discussions](/discussions/collaborating-with-your-community-using-discussions/about-discussions#about-categories-and-formats-for-discussions)."  1. Click **Create**.  ### Editing a category You can edit a category to change the category's emoji, title, description, and discussion format. {% data reusables.repositories.navigate-to-repo %} {% data reusables.discussions.discussions-tab %} 1. To the right of a category in the list, click {% octicon "pencil" aria-label="The pencil icon" %}.  1. {% data reusables.discussions.edit-category-details %}  1. Click **Save changes**.  ### Deleting a category When you delete a category, {% data variables.product.product_name %} will move all discussions in the deleted category to an existing category that you choose. {% data reusables.repositories.navigate-to-repo %} {% data reusables.discussions.discussions-tab %} 1. To the right of a category in the list, click {% octicon "trash" aria-label="The trash icon" %}.  1. Use the drop-down menu, and choose a new category for any discussions in the category you're deleting.  1. Click **Delete & Move**.  108 ...aging-discussions-for-your-community/managing-discussions-in-your-repository.md @@ -0,0 +1,108 @@ --- title: Managing discussions in your repository intro: You can categorize, spotlight, transfer, or delete the discussions in a repository. permissions: Repository administrators and people with write or greater access to a repository can manage discussions in the repository. versions: free-pro-team: '*' --- {% data reusables.discussions.beta %} ### About management of discussions {% data reusables.discussions.about-discussions %} For more information about discussions, see "[About discussions](/discussions/collaborating-with-your-community-using-discussions/about-discussions)." Organization owners can choose the permissions required to create a discussion for repositories owned by the organization. For more information, see "[Managing discussion creation for repositories in your organization](/github/setting-up-and-managing-organizations-and-teams/managing-discussion-creation-for-repositories-in-your-organization)." As a discussions maintainer, you can create community resources to encourage discussions that are aligned with the overall project goal and maintain a friendly open forum for collaborators. Creating a code of conduct or contribution guidelines for collaborators to follow will help facilitate a collaborative and productive forum. For more information on creating community resources, see "[Adding a code of conduct to your project](/github/building-a-strong-community/adding-a-code-of-conduct-to-your-project)," and "[Setting guidelines for repository contributors](/github/building-a-strong-community/setting-guidelines-for-repository-contributors)." For more information on facilitating a healthy discussion, see "[Moderating comments and conversations](/github/building-a-strong-community/moderating-comments-and-conversations)." ### Prerequisites To manage discussions in a repository, discussions must be enabled for the repository. For more information, see "[Enabling or disabling discussions for a repository](/github/administering-a-repository/enabling-or-disabling-github-discussions-for-a-repository)." ### Changing the category for a discussion You can categorize discussions to help community members find related discussions. For more information, see "[Managing categories for discussions in your repository](/discussions/managing-discussions-for-your-community/managing-categories-for-discussions-in-your-repository)" article. You can also move a discussion to a different category. {% data reusables.repositories.navigate-to-repo %} {% data reusables.discussions.discussions-tab %} {% data reusables.discussions.click-discussion-in-list %} 1. In the right sidebar, click {% octicon "pencil" aria-label="The pencil icon" %} **Edit pinned discussion**.  ### Pinning a discussion You can pin up to four important discussions above the list of discussions for the repository. {% data reusables.repositories.navigate-to-repo %} {% data reusables.discussions.discussions-tab %} {% data reusables.discussions.click-discussion-in-list %} 1. In the right sidebar, click {% octicon "pin" aria-label="The pin icon" %} **Pin discussion**.  1. Optionally, customize the look of the pinned discussion.  1. Click **Pin discussion**.  ### Editing a pinned discussion Editing a pinned discussion will not change the discussion's category. For more information, see "[Managing categories for discussions in your repository](/discussions/managing-discussions-for-your-community/managing-categories-for-discussions-in-your-repository)." {% data reusables.repositories.navigate-to-repo %} {% data reusables.discussions.discussions-tab %} {% data reusables.discussions.click-discussion-in-list %} 1. In the right sidebar, click {% octicon "pencil" aria-label="The pencil icon" %} **Edit pinned discussion**.  1. Customize the look of the pinned discussion.  1. Click **Pin discussion**.  ### Unpinning a discussion {% data reusables.repositories.navigate-to-repo %} {% data reusables.discussions.discussions-tab %} {% data reusables.discussions.click-discussion-in-list %} 1. In the right sidebar, click {% octicon "pin" aria-label="The pin icon" %} **Unpin discussion**.  1. Read the warning, then click **Unpin discussion**.  ### Transferring a discussion To transfer a discussion, you must have permissions to create discussions in the repository where you want to transfer the discussion. {% data reusables.repositories.navigate-to-repo %} {% data reusables.discussions.discussions-tab %} {% data reusables.discussions.click-discussion-in-list %} 1. In the right sidebar, click {% octicon "arrow-right" aria-label="The right arrow icon" %} **Transfer discussion**.  1. Select the **Choose a repository** drop-down, and click the repository you want to transfer the discussion to.  1. Click **Transfer discussion**.  ### Deleting a discussion {% data reusables.repositories.navigate-to-repo %} {% data reusables.discussions.discussions-tab %} {% data reusables.discussions.click-discussion-in-list %} 1. In the right sidebar, click {% octicon "trash" aria-label="The trash arrow icon" %} **Delete discussion**.  1. Read the warning, then click **Delete this discussion**.  ### Converting issues based on labels You can convert all issues with the same label to discussions in bulk. Future issues with this label will also automatically convert to the discussion and category you configure. {% data reusables.repositories.navigate-to-repo %} {% data reusables.repositories.sidebar-issues %} {% data reusables.project-management.labels %} 1. Next to the label you want to convert to issues, click **Convert issues**. 1. Select the **Choose a category** drop-down menu, and click a category for your discussion. 1. Click **I understand, convert this issue to a discussion**. 40 ...t/discussions/managing-discussions-for-your-community/moderating-discussions.md @@ -0,0 +1,40 @@ --- title: Moderating discussions intro: 'You can promote healthy collaboration by marking comments as answers, locking or unlocking discussions, and converting issues to discussions. and editing or deleting comments, discussions, and categories that don''t align with your community''s code of conduct to discussions.' permissions: People with triage access to a repository can moderate discussions in the repository. versions: free-pro-team: '*' --- {% data reusables.discussions.beta %} ### About moderating discussions {% data reusables.discussions.about-discussions %} If you have triage permissions for a repository, you can help moderate a project's discussions by marking comments as answers, locking discussions that are not longer useful or are damaging to the community, and converting issues to discussions when an idea is still in the early stages of development. ### Marking a comment as an answer {% data reusables.discussions.marking-a-comment-as-an-answer %} ### Locking discussions It's appropriate to lock a conversation when the entire conversation is not constructive or violates your community's code of conduct or {% data variables.product.prodname_dotcom %}'s [Community Guidelines](/github/site-policy/github-community-guidelines). You can also lock a conversation to prevent comments on a discussion you want to use as an announcement to the community. When you lock a conversation, people with write access to the repository will still be able to comment on the discussion. {% data reusables.repositories.navigate-to-repo %} {% data reusables.discussions.discussions-tab %} 1. In the list of discussions, click the discussion you want to lock.  1. In the right margin of a discussion, click **Lock conversation**. 1. Read the information about locking conversations and click **Lock conversation on this discussion**. 1. When you're ready to unlock the conversation, click **Unlock conversation**, then click **Unlock conversation on this discussion**. ### Converting an issue to a discussion When you convert an issue to a discussion, the discussion is automatically created using the content from the issue. People with write access to a repository can bulk convert issues based on labels. For more information, see "[Managing discussions in your repository](/discussions/managing-discussions-for-your-community/managing-discussions-in-your-repository)." {% data reusables.repositories.navigate-to-repo %} {% data reusables.repositories.sidebar-issues %} 1. In the list of issues, click the issue you'd like to convert. 1. In the right margin of an issue, click **Convert to discussion**. 1. Select the **Choose a category** drop-down menu, and click a category for your discussion. 1. Click **I understand, convert this issue to a discussion**. 62 content/discussions/quickstart.md @@ -0,0 +1,62 @@ --- title: Quickstart for GitHub Discussions intro: 'Enable {% data variables.product.prodname_discussions %} on an existing repository and start conversations with your community.' allowTitleToDifferFromFilename: true versions: free-pro-team: '*' --- {% data reusables.discussions.beta %} ### Introduction {% data variables.product.prodname_discussions %} is a collaborative communication forum for the community around an open source project. Discussions are for conversations that need to be transparent and accessible but do not need to be tracked on a project board and are not related to code, unlike issues. Discussions enable fluid, open conversation in a public forum. Discussions give a space for more collaborative conversations by connecting and giving a more centralized area to connect and find information. ### Enabling {% data variables.product.prodname_discussions %} on your repository Repository owners and people with write access can enable {% data variables.product.prodname_discussions %} for a community on their public repositories. When you first enable a {% data variables.product.prodname_discussions %}, you will be invited to configure a welcome post. {% data reusables.repositories.navigate-to-repo %} 1. Under your repository name, click {% octicon "gear" aria-label="The gear icon" %} **Settings**.  1. Under "Features", click **Set up discussions**.  1. Under "Start a new discussion," edit the template to align with the resources and tone you want to set for your community. 1. Click **Start discussion**.  ### Welcoming contributions to your discussions You can welcome your community and introduce a new way to communicate in a repository by creating a welcome post and pin the post to your {% data variables.product.prodname_discussions %} page. Pinning and locking discussions helps people know that a post is meant as an announcement. You can use announcements as a way to link people to more resources and offer guidance for opening discussions in your community. For more information about pinning a discussion, see "[Managing discussions in your repository](/discussions/managing-discussions-for-your-community/managing-discussions-in-your-repository#pinning-a-discussion)." ### Setting up community guidelines for contributors You can set contributing guidelines to encourage collaborators to have meaningful, useful conversations that are relevant to the repository. You can also update the repository's README to communicate expectations on when collaborators should open an issue or discussion. For more information about providing guidelines for your project, see "[Adding a code of conduct to your project](/github/building-a-strong-community/adding-a-code-of-conduct-to-your-project)" and "[Setting up your project for healthy contributions](/github/building-a-strong-community/setting-up-your-project-for-healthy-contributions)." ### Creating a new discussion Anyone with access to a repository can create a discussion. {% data reusables.discussions.starting-a-discussion %} ### Organizing discussions into relevant categories Repository owners and people with write access can create new categories to keep discussions organized. Collaborators participating and creating new discussions can group discussions into the most relevant existing categories. Discussions can also be recategorized after they are created. For more information, see "[Managing categories for discussions in your repository](/discussions/managing-discussions-for-your-community/managing-categories-for-discussions-in-your-repository)" ### Promoting healthy conversations People with write permissions for a repository can help surface important conversations by pinning discussions, deleting discussions that are no longer useful or are damaging to the community, and transferring discussions to more relevant repositories owned by the organization. For more information, see "[Managing discussions in your repository](/discussions/managing-discussions-for-your-community/managing-discussions-in-your-repository)." People with triage permissions for a repository can help moderate a project's discussions by marking comments as answers, locking discussions that are not longer useful or are damaging to the community, and converting issues to discussions when an idea is still in the early stages of development. For more information, see "[Moderating discussions](/discussions/managing-discussions-for-your-community/moderating-discussions)." ### Next steps Once there is a clear path to scope work out and move an idea from concept to reality, you can create an issue and start tracking your progress. For more information on creating an issue from a discussion, see "[Moderating discussions](/discussions/managing-discussions-for-your-community/moderating-discussions)." 45 content/education/guides.md @@ -0,0 +1,45 @@ --- title: Guides for GitHub Education intro: 'These guides for {% data variables.product.prodname_education %} help you teach and learn both {% data variables.product.product_name %} and software development.' allowTitleToDifferFromFilename: true versions: free-pro-team: '*' --- ### Get started with {% data variables.product.product_name %} Teachers, students, and researchers can use tools from {% data variables.product.product_name %} to enrich a software development curriculum and develop real-world collaboration skills. - [Sign up for a new {% data variables.product.prodname_dotcom %} account](/github/getting-started-with-github/signing-up-for-a-new-github-account) - [Git and {% data variables.product.prodname_dotcom %} quickstart ](/github/getting-started-with-github/quickstart) - [Apply for an educator or researcher discount](/education/teach-and-learn-with-github-education/apply-for-an-educator-or-researcher-discount) - [Apply for a student developer pack](/education/teach-and-learn-with-github-education/apply-for-a-student-developer-pack) ### Run a software development course with {% data variables.product.company_short %} Administer a classroom, assign and review work from your students, and teach the new generation of software developers with {% data variables.product.prodname_classroom %}. - [Basics of setting up {% data variables.product.prodname_classroom %} ](/education/manage-coursework-with-github-classroom/basics-of-setting-up-github-classroom) - [Manage classrooms](/education/manage-coursework-with-github-classroom/manage-classrooms) - [Create an individual assignment](/education/manage-coursework-with-github-classroom/create-an-individual-assignment) - [Create a group assignment](/education/manage-coursework-with-github-classroom/create-a-group-assignment) - [Create an assignment from a template repository](/education/manage-coursework-with-github-classroom/create-an-assignment-from-a-template-repository) - [Leave feedback with pull requests](/education/manage-coursework-with-github-classroom/leave-feedback-with-pull-requests) - [Use autograding](/education/manage-coursework-with-github-classroom/use-autograding) ### Learn to develop software Incorporate {% data variables.product.prodname_dotcom %} into your education, and use the same tools as the professionals. - [Git and {% data variables.product.prodname_dotcom %} learning resources](/github/getting-started-with-github/git-and-github-learning-resources) - [Use {% data variables.product.prodname_dotcom %} for your schoolwork](/education/teach-and-learn-with-github-education/use-github-for-your-schoolwork) - [Try {% data variables.product.prodname_desktop %}](/desktop) - [Try {% data variables.product.prodname_cli %}](/github/getting-started-with-github/github-cli) ### Contribute to the community Participate in the community, get training from {% data variables.product.company_short %}, and learn or teach new skills. - [{% data variables.product.prodname_education_community %}](https://education.github.community) - [About Campus Experts](/education/teach-and-learn-with-github-education/about-campus-experts) - [About Campus Advisors](/education/teach-and-learn-with-github-education/about-campus-advisors) 43 content/education/index.md @@ -0,0 +1,43 @@ --- title: GitHub Education Documentation shortTitle: Education intro: "{% data variables.product.prodname_education %} helps you teach or learn software development with the tools and support of {% data variables.product.company_short %}'s platform and community." introLinks: quickstart: /education/quickstart featuredLinks: guides: - /education/teach-and-learn-with-github-education/apply-for-a-student-developer-pack - /education/teach-and-learn-with-github-education/apply-for-an-educator-or-researcher-discount - /education/teach-and-learn-with-github-education/use-github-at-your-educational-institution guideCards: - /github/getting-started-with-github/signing-up-for-a-new-github-account - /github/getting-started-with-github/git-and-github-learning-resources - /education/manage-coursework-with-github-classroom/basics-of-setting-up-github-classroom popular: - /education/teach-and-learn-with-github-education/use-github-for-your-schoolwork - /education/teach-and-learn-with-github-education/use-github-in-your-classroom-and-research - /desktop - /github/getting-started-with-github/github-cli - /education/manage-coursework-with-github-classroom/teach-with-github-classroom changelog: - title: 'Try something new at Local Hack Day: Learn' date: '2020-10-15' href: https://github.blog/2020-10-15-try-something-new-at-local-hack-day-learn/ - title: 'Remote Education: Creating community through shared experiences' date: '2020-09-24' href: https://github.blog/2020-09-24-remote-education-creating-community-through-shared-experiences/ - title: 'Remote Education: A series of best practices for online campus communities' date: '2020-09-10' href: https://github.blog/2020-09-10-remote-education-a-series-of-best-practices-for-online-campus-communities/ - title: Welcome to the inaugural class of MLH Fellows date: '2020-06-24' href: https://github.blog/2020-06-24-welcome-to-the-inaugural-class-of-mlh-fellows/ layout: product-landing versions: free-pro-team: '*' --- <!-- {% link_with_intro /teach-and-learn-with-github-education %} --> <!-- {% link_with_intro /manage-coursework-with-github-classroom %} --> 31 ...work-with-github-classroom/about-using-makecode-arcade-with-github-classroom.md @@ -0,0 +1,31 @@ --- title: About using MakeCode Arcade with GitHub Classroom shortTitle: About using MakeCode Arcade intro: You can configure MakeCode Arcade as the online IDE for assignments in {% data variables.product.prodname_classroom %}. versions: free-pro-team: '*' redirect_from: - /education/manage-coursework-with-github-classroom/student-experience-makecode --- ### About MakeCode Arcade MakeCode Arcade is an online integrated development environment (IDE) for developing retro arcade games using drag-and-drop block programming and JavaScript. Students can write, edit, run, test, and debug code in a browser with MakeCode Arcade. For more information about online IDEs and {% data variables.product.prodname_classroom %}, see "[Integrate {% data variables.product.prodname_classroom %} with an online IDE](/education/manage-coursework-with-github-classroom/integrate-github-classroom-with-an-online-ide)." {% data reusables.classroom.readme-contains-button-for-online-ide %} The first time the student clicks the button to visit MakeCode Arcade, the student must sign into MakeCode Arcade with {% data variables.product.product_name %} credentials. After signing in, the student will have access to a development environment containing the code from the assignment repository, fully configured on MakeCode Arcade. For more information about working on MakeCode Arcade, see the [MakeCode Arcade Tour](https://arcade.makecode.com/ide-tour) and [documentation](https://arcade.makecode.com/docs) on the MakeCode Arcade website. MakeCode Arcade does not support multiplayer-editing for group assignments. Instead, students can collaborate with Git and {% data variables.product.product_name %} features like branches and pull requests. ### About submission of assignments with MakeCode Arcade By default, MakeCode Arcade is configured to push to the assignment repository on {% data variables.product.product_location %}. After making progress on an assignment with MakeCode Arcade, students should push changes to {% data variables.product.product_location %} using the {% octicon "mark-github" aria-label="The GitHub mark" %}{% octicon "arrow-up" aria-label="The up arrow icon" %} button at the bottom of the screen.  ### Further reading - "[About READMEs](/github/creating-cloning-and-archiving-repositories/about-readmes)" 33 ...ge-coursework-with-github-classroom/about-using-replit-with-github-classroom.md @@ -0,0 +1,33 @@ --- title: About using Repl.it with GitHub Classroom shortTitle: About using Repl.it intro: You can configure Repl.it as the online integrated development environment (IDE) for assignments in {% data variables.product.prodname_classroom %}. versions: free-pro-team: '*' redirect_from: - /education/manage-coursework-with-github-classroom/student-experience-replit --- ### About Repl.it Repl.it is an online integrated development environment (IDE) that supports multiple programming languages. Students can write, edit, run, test, and debug code in a browser with Repl.it. For more information about online IDEs and {% data variables.product.prodname_classroom %}, see "[Integrate {% data variables.product.prodname_classroom %} with an online IDE](/education/manage-coursework-with-github-classroom/integrate-github-classroom-with-an-online-ide)." {% data reusables.classroom.readme-contains-button-for-online-ide %} The first time the student clicks the button to visit Repl.it, the student must sign into Repl.it with {% data variables.product.product_name %} credentials. After signing in, the student will have access to a development environment containing the code from the assignment repository, fully configured on Repl.it. For more information about working on Repl.it, see the [Repl.it Quickstart Guide](https://docs.repl.it/misc/quick-start#the-repl-environment). For group assignments, students can use Repl.it Multiplayer to work collaboratively. For more information, see the [Repl.it Multiplayer](https://repl.it/site/multiplayer) website. ### About submission of assignments with Repl.it By default, Repl.it is configured to push to the assignment repository on {% data variables.product.product_location %}. After making progress on an assignment with Repl.it, students should push changes to {% data variables.product.product_location %} using the version control functionality in the left sidebar.  For more information about using Git on Repl.it, see the [Repl.it + Git Tutorial](https://repl.it/talk/learn/Replit-Git-Tutorial/23331) on the Repl.it website. ### Further reading - "[About READMEs](/github/creating-cloning-and-archiving-repositories/about-readmes)" 33 ...anage-coursework-with-github-classroom/basics-of-setting-up-github-classroom.md @@ -0,0 +1,33 @@ --- title: Basics of setting up GitHub Classroom shortTitle: '{% data variables.product.prodname_classroom %} basics' intro: Learn how to set up your classroom, manage assignments, and configure time-saving automation. versions: free-pro-team: '*' --- ### Videos about {% data variables.product.prodname_classroom %} You can watch a series of short video tutorials about the configuration and use of {% data variables.product.prodname_classroom %}. To watch all videos as part of a continuous playlist, see the [{% data variables.product.prodname_classroom %} Getting Started Guide](https://www.youtube.com/playlist?list=PLIRjfNq867bewk3ZGV6Z7a16YDNRCpK3u) on YouTube. For more information about terminology for {% data variables.product.prodname_classroom %}, see "[Glossary](/education/manage-coursework-with-github-classroom/glossary)". 1. <a href="https://youtu.be/xVVeqIDgCvM" target="_blank">Getting started</a> {% octicon "link-external" aria-label="The external link icon" %} 2. <a href="https://youtu.be/DTzrKduaHj8" target="_blank">Adding your student roster</a> {% octicon "link-external" aria-label="The external link icon" %} 3. Creating assignments - <a href="https://youtu.be/6QzKZ63KLss" target="_blank">Creating an assignment using a {% data variables.product.prodname_dotcom %} repository</a> {% octicon "link-external" aria-label="The external link icon" %} - <a href="https://youtu.be/Qmwh6ijsQJU" target="_blank">Creating an assignment using Microsoft MakeCode as your online IDE</a> {% octicon "link-external" aria-label="The external link icon" %} - <a href="https://youtu.be/p_g5sQ7hUis" target="_blank">Creating an assignment using Repl.it as your online IDE</a> {% octicon "link-external" aria-label="The external link icon" %} 4. <a href="https://youtu.be/ObaFRGp_Eko" target="_blank">How students complete assignments</a> {% octicon "link-external" aria-label="The external link icon" %} 5. <a href="https://youtu.be/g45OJn3UyCU" target="_blank">How teachers review assignments</a> {% octicon "link-external" aria-label="The external link icon" %} 6. <a href="https://youtu.be/QxrA3taZdNM" target="_blank">Creating group assignments</a> {% octicon "link-external" aria-label="The external link icon" %} 7. <a href="https://youtu.be/tJK2cmoh1KM" target="_blank">Next steps to get started</a> {% octicon "link-external" aria-label="The external link icon" %} 8. <a href="https://youtu.be/X87v3SFQxLU" target="_blank">{% data variables.product.prodname_dotcom %} Teacher Toolbox</a> {% octicon "link-external" aria-label="The external link icon" %} ### Next steps For more information about teaching with {% data variables.product.prodname_classroom %}, see "[Teach with {% data variables.product.prodname_classroom %}](/education/manage-coursework-with-github-classroom/teach-with-github-classroom)." ### Further reading - "[Teach and learn with {% data variables.product.prodname_education %}](/education/teach-and-learn-with-github-education)" 51 ...with-github-classroom/configure-default-settings-for-assignment-repositories.md @@ -0,0 +1,51 @@ --- title: Configure default settings for assignment repositories shortTitle: Configure defaults for assignment repositories intro: You can use the Probot Settings app to configure the default settings for repositories that {% data variables.product.prodname_classroom %} creates for an assignment. permissions: Organization owners can configure default settings for assignment repositories by installing a {% data variables.product.prodname_github_app %} for the organization. versions: free-pro-team: '*' redirect_from: - /education/manage-coursework-with-github-classroom/probot-settings --- ### About configuration of defaults for assignment repositories {% data variables.product.prodname_classroom %} creates a repository that belongs for each student or team that accepts an assignment. The repository belongs to the organization that you use for {% data variables.product.prodname_classroom %}. Assignment repositories can be empty, or you can use a template repository. For more information, see "[Create an assignment from a template repository](/education/manage-coursework-with-github-classroom/create-an-assignment-from-a-template-repository)." {% data reusables.classroom.you-may-want-to-predefine-repository-settings %} With the Probot Settings app, you can create a file named _.github/settings.yml_ in a repository that contains a list of settings for the repository, and then install a {% data variables.product.prodname_github_app %} for your organization that automatically applies the settings to the repository. You can include _.github/settings.yml_ in a template repository that you use for an assignment in {% data variables.product.prodname_classroom %}. When an individual or team accepts the assignment, {% data variables.product.prodname_classroom %} creates the assignment repository, and the Settings app automatically applies the settings from _.github/settings.yml_. Probot is a a project, framework, and collection of free apps to automate {% data variables.product.product_name %}. A Probot app can listen to repository events, like the creation of new commits, comments, and issues, and automatically respond to the event. For more information, see the [Probot website](https://probot.github.io) and the [Settings app website](https://probot.github.io/apps/settings/). For more information about {% data variables.product.prodname_github_apps %}, see "[About apps](/developers/apps/about-apps)." ### Adding the Settings app to your organization After you install the Probot Settings app for your organization, the app will apply the settings that you define in _.github/settings.yml_ for any repository in your organization, including new assignment repositories that {% data variables.product.prodname_classroom %} creates. 1. Navigate to the [Settings app page](https://github.com/apps/settings). 1. Click **Install**, then click the organization that you use for {% data variables.product.prodname_classroom %}. Provide the app full access to all repositories owned by the organization.  ### Configuring default settings for an assignment repository 1. Create a template repository that contains a _.github/settings.yml_ file. For a complete list of settings, see the [README](https://github.com/probot/settings#github-settings) for the `probot/settings` repository. For more information about using a template repository for starter code in {% data variables.product.prodname_classroom %}, see "[Create an assignment from a template repository](/education/manage-coursework-with-github-classroom/create-an-assignment-from-a-template-repository)." {% warning %} **Warning:** Do not define `collaborators` in the _.github/settings.yml_ file for your template repository. {% data variables.product.prodname_classroom %} automatically grants teachers and teaching assistants access to assignment repositories. {% endwarning %} 1. Create an assignment using the template repository containing _.github/settings.yml_ as the starter code. {% data reusables.classroom.for-more-information-about-assignment-creation %} The Probot Settings app for your organization will now apply the settings you define in _.github/settings.yml_ within the template repository to every assignment repository that {% data reusables.classroom.you-may-want-to-predefine-repository-settings %} creates for a student or team. ### Further reading - [Probot apps](https://probot.github.io/apps/) - [Probot documentation](https://probot.github.io/docs/) 142 ...th-github-classroom/connect-a-learning-management-system-to-github-classroom.md @@ -0,0 +1,142 @@ --- title: Connect a learning management system to GitHub Classroom intro: You can configure an LTI-compliant learning management system (LMS) to connect to {% data variables.product.prodname_classroom %} so that you can import a roster for your classroom. versions: free-pro-team: '*' redirect_from: - /education/manage-coursework-with-github-classroom/configuring-a-learning-management-system-for-github-classroom - /education/manage-coursework-with-github-classroom/connect-to-lms - /education/manage-coursework-with-github-classroom/generate-lms-credentials - /education/manage-coursework-with-github-classroom/setup-canvas - /education/manage-coursework-with-github-classroom/setup-generic-lms - /education/manage-coursework-with-github-classroom/setup-moodle --- ### About configuration of your LMS You can connect a learning management system (LMS) to {% data variables.product.prodname_classroom %}, and {% data variables.product.prodname_classroom %} can import a roster of student identifiers from the LMS. To connect your LMS to {% data variables.product.prodname_classroom %}, you must enter configuration credentials for {% data variables.product.prodname_classroom %} in your LMS. ### Prerequisites To configure an LMS to connect to {% data variables.product.prodname_classroom %}, you must first create a classroom. For more information, see "[Manage classrooms](/education/manage-coursework-with-github-classroom/manage-classrooms#creating-a-classroom)." ### Supported LMSes {% data variables.product.prodname_classroom %} supports import of roster data from LMSes that implement Learning Tools Interoperability (LTI) standards. - LTI version 1.0 and/or 1.1 - LTI Names and Roles Provisioning 1.X Using LTI helps keep your information safe and secure. LTI is an industry-standard protocol and GitHub Classroom's use of LTI is certified by the Instructional Management System (IMS) Global Learning Consortium. For more information, see [Learning Tools Interoperability](https://www.imsglobal.org/activity/learning-tools-interoperability) and [About IMS Global Learning Consortium](http://www.imsglobal.org/aboutims.html) on the IMS Global Learning Consortium website. {% data variables.product.company_short %} has tested import of roster data from the following LMSes into {% data variables.product.prodname_classroom %}. - Canvas - Google Classroom - Moodle - Sakai Currently, {% data variables.product.prodname_classroom %} doesn't support import of roster data from Blackboard or Brightspace ### Generating configuration credentials for your classroom {% data reusables.classroom.sign-into-github-classroom %} {% data reusables.classroom.click-classroom-in-list %} {% data reusables.classroom.click-students %} 1. If your classroom already has a roster, you can either update the roster or delete the roster and create a new roster. - For more information about deleting and creating a roster, see "[Deleting a roster for a classroom](/education/manage-coursework-with-github-classroom/manage-classrooms#deleting-a-roster-for-a-classroom)" and "[Creating a roster for your classroom](/education/manage-coursework-with-github-classroom/manage-classrooms#creating-a-roster-for-your-classroom)." - For more information about updating a roster, see "[Adding students to the roster for your classroom](/education/manage-coursework-with-github-classroom/manage-classrooms#adding-students-to-the-roster-for-your-classroom)." 1. In the list of LMSes, click your LMS. If your LMS is not supported, click **Other LMS**.  1. Read about connecting your LMS, then click **Connect to _LMS_**. 1. Copy the "Consumer Key", "Shared Secret", and "Launch URL" for the connection to the classroom.  ### Configuring a generic LMS You must configure the privacy settings for your LMS to allow external tools to receive roster information. 1. Navigate to your LMS. 1. Configure an external tool. 1. Provide the configuration credentials you generated in {% data variables.product.prodname_classroom %}. - Consumer key - Shared secret - Launch URL (sometimes called "tool URL" or similar) ### Configuring Canvas You can configure {% data variables.product.prodname_classroom %} as an external app for Canvas to import roster data into your classroom. For more information about Canvas, see the [Canvas website](https://www.instructure.com/canvas/). 1. Sign into [Canvas](https://www.instructure.com/canvas/#login). 1. Select the Canvas course to integrate with {% data variables.product.prodname_classroom %}. 1. In the left sidebar, click **Settings**. 1. Click the **Apps** tab. 1. Click **View app configurations**. 1. Click **+App**. 1. Select the **Configuration Type** drop-down menu, and click **By URL**. 1. Paste the configuration credentials from {% data variables.product.prodname_classroom %}. For more information, see "[Generating configuration credentials for your classroom](#generating-configuration-credentials-for-your-classroom)." | Field in Canvas app configuration | Value or setting | | :- | :- | | **Consumer Key** | Consumer key from {% data variables.product.prodname_classroom %} | | **Shared Secret** | Shared secret from {% data variables.product.prodname_classroom %} | | **Allow this tool to access the IMS Names and Role Provisioning Service** | Enabled | | **Configuration URL** | Launch URL from {% data variables.product.prodname_classroom %} | {% note %} **Note**: If you don't see a checkbox in Canvas labeled "Allow this tool to access the IMS Names and Role Provisioning Service", then your Canvas administrator must contact Canvas support to enable membership service configuration for your Canvas account. Without enabling this feature, you won't be able to sync the roster from Canvas. For more information, see [How do I contact Canvas Support?](https://community.canvaslms.com/t5/Canvas-Basics-Guide/How-do-I-contact-Canvas-Support/ta-p/389767) on the Canvas website. {% endnote %} 1. Click **Submit**. 1. In the left sidebar, click **Home**. 1. To prompt Canvas to send a confirmation email, in the left sidebar, click **GitHub Classroom**. Follow the instructions in the email to finish linking {% data variables.product.prodname_classroom %}. ### Configuring Moodle You can configure {% data variables.product.prodname_classroom %} as an activity for Moodle to import roster data into your classroom. For more information about Moodle, see the [Moodle website](https://moodle.org). You must be using Moodle version 3.0 or greater. 1. Sign into [Moodle](https://moodle.org/login/index.php). 1. Select the Moodle course to integrate with {% data variables.product.prodname_classroom %}. 1. Click **Turn editing on**. 1. Wherever you'd like {% data variables.product.prodname_classroom %} to be available in Moodle, click **Add an activity or resource**. 1. Choose **External tool** and click **Add**. 1. In the "Activity name" field, type "GitHub Classroom". 1. In the **Preconfigured tool** field, to the right of the drop-down menu, click **+**. 1. Under "External tool configuration", paste the configuration credentials from {% data variables.product.prodname_classroom %}. For more information, see "[Generating configuration credentials for your classroom](#generating-configuration-credentials-for-your-classroom)." | Field in Moodle app configuration | Value or setting | | :- | :- | | **Tool name** | {% data variables.product.prodname_classroom %} - _YOUR CLASSROOM NAME_<br/><br/>**Note**: You can use any name, but we suggest this value for clarity. | | **Tool URL** | Launch URL from {% data variables.product.prodname_classroom %} | | **LTI version** | LTI 1.0/1.1 | | **Default launch container** | New window | | **Consumer key** | Consumer key from {% data variables.product.prodname_classroom %} | | **Shared secret** | Shared secret from {% data variables.product.prodname_classroom %} | 1. Scroll to and click **Services**. 1. To the right of "IMS LTI Names and Role Provisioning", select the drop-down menu and click **Use this service to retrieve members' information as per privacy settings**. 1. Scroll to and click **Privacy**. 1. To the right of **Share launcher's name with tool** and **Share launcher's email with tool**, select the drop-down menus to click **Always**. 1. At the bottom of the page, click **Save changes**. 1. In the **Preconfigure tool** menu, click **GitHub Classroom - _YOUR CLASSROOM NAME_**. 1. Under "Common module settings", to the right of "Availability", select the drop-down menu and click **Hide from students**. 1. At the bottom of the page, click **Save and return to course**. 1. Navigate to anywhere you chose to display {% data variables.product.prodname_classroom %}, and click the {% data variables.product.prodname_classroom %} activity. ### Importing a roster from your LMS For more information about importing the roster from your LMS into {% data variables.product.prodname_classroom %}, see "[Manage classrooms](/education/manage-coursework-with-github-classroom/manage-classrooms#creating-a-roster-for-your-classroom)." ### Disconnecting your LMS {% data reusables.classroom.sign-into-github-classroom %} {% data reusables.classroom.click-classroom-in-list %} {% data reusables.classroom.click-settings %} 1. Under "Connect to a learning management system (LMS)", click **Connection Settings**.  1. Under "Delete Connection to your learning management system", click **Disconnect from your learning management system**.  145 .../education/manage-coursework-with-github-classroom/create-a-group-assignment.md @@ -0,0 +1,145 @@ --- title: Create a group assignment intro: 'You can create a collaborative assignment for teams of students who participate in your course.' versions: free-pro-team: '*' redirect_from: - /education/manage-coursework-with-github-classroom/create-group-assignments --- ### About group assignments {% data reusables.classroom.assignments-group-definition %} Students can work together on a group assignment in a shared repository, like a team of professional developers. When a student accepts a group assignment, the student can create a new team or join an existing team. {% data variables.product.prodname_classroom %} saves the teams for an assignment as a set. You can name the set of teams for a specific assignment when you create the assignment, and you can reuse that set of teams for a later assignment. {% data reusables.classroom.classroom-creates-group-repositories %} {% data reusables.classroom.about-assignments %} You can decide how many teams one assignment can have, and how many members each team can have. Each team that a student creates for an assignment is a team within your organization on {% data variables.product.product_name %}. The visibility of the team is secret. Teams that you create on {% data variables.product.product_name %} will not appear in {% data variables.product.prodname_classroom %}. For more information, see "[About teams](/github/setting-up-and-managing-organizations-and-teams/about-teams)." For a video demonstration of the creation of a group assignment, see "[Basics of setting up {% data variables.product.prodname_classroom %}](/education/manage-coursework-with-github-classroom/basics-of-setting-up-github-classroom)." ### Prerequisites {% data reusables.classroom.assignments-classroom-prerequisite %} ### Creating an assignment {% data reusables.classroom.assignments-guide-create-the-assignment %} ### Setting up the basics for an assignment Name your assignment, decide whether to assign a deadline, define teams, and choose the visibility of assignment repositories. - [Naming an assignment](#naming-an-assignment) - [Assigning a deadline for an assignment](#assigning-a-deadline-for-an-assignment) - [Choosing an assignment type](#choosing-an-assignment-type) - [Defining teams for an assignment](#defining-teams-for-an-assignment) - [Choosing a visibility for assignment repositories](#choosing-a-visibility-for-assignment-repositories) #### Naming an assignment For a group assignment, {% data variables.product.prodname_classroom %} names repositories by the repository prefix and the name of the team. By default, the repository prefix is the assignment title. For example, if you name an assignment "assignment-1" and the team's name on {% data variables.product.product_name %} is "student-team", the name of the assignment repository for members of the team will be `assignment-1-student-team`. {% data reusables.classroom.assignments-type-a-title %} #### Assigning a deadline for an assignment {% data reusables.classroom.assignments-guide-assign-a-deadline %} #### Choosing an assignment type Under "Individual or group assignment", select the drop-down menu, then click **Group assignment**. You can't change the assignment type after you create the assignment. If you'd rather create a individual assignment, see "[Create an individual assignment](/education/manage-coursework-with-github-classroom/create-an-individual-assignment)." #### Defining teams for an assignment If you've already created a group assignment for the classroom, you can reuse a set of teams for the new assignment. To create a new set with the teams that your students create for the assignment, type the name for the set. Optionally, type the maximum number of team members and total teams. {% tip %} **Tips**: - We recommend including details about the set of teams in the name for the set. For example, if you want to use the set of teams for one assignment, name the set after the assignment. If you want to reuse the set throughout a semester or course, name the set after the semester or course. - If you'd like to assign students to a specific team, give your students a name for the team and provide a list of members. {% endtip %}  #### Choosing a visibility for assignment repositories {% data reusables.classroom.assignments-guide-choose-visibility %} {% data reusables.classroom.assignments-guide-click-continue-after-basics %} ### Adding starter code and configuring a development environment {% data reusables.classroom.assignments-guide-intro-for-environment %} - [Choosing a template repository](#choosing-a-template-repository) - [Choosing an online integrated development environment (IDE)](#choosing-an-online-integrated-development-environment-ide) #### Choosing a template repository By default, a new assignment will create an empty repository for each team that a student creates. {% data reusables.classroom.you-can-choose-a-template-repository %} For more information about template repositories, see "[Creating a template repository](/github/creating-cloning-and-archiving-repositories/creating-a-template-repository)." {% data reusables.classroom.assignments-guide-choose-template-repository %} #### Choosing an online integrated development environment (IDE) {% data reusables.classroom.about-online-ides %} For more information, see "[Integrate {% data variables.product.prodname_classroom %} with an IDE](/education/manage-coursework-with-github-classroom/integrate-github-classroom-with-an-ide)." {% data reusables.classroom.assignments-guide-choose-an-online-ide %} {% data reusables.classroom.assignments-guide-click-continue-after-starter-code-and-feedback %} ### Providing feedback Optionally, you can automatically grade assignments and create a space for discussing each submission with the team. - [Testing assignments automatically](#testing-assignments-automatically) - [Preventing changes to important files](#preventing-changes-to-important-files) - [Creating a pull request for feedback](#creating-a-pull-request-for-feedback) #### Testing assignments automatically {% data reusables.classroom.assignments-guide-using-autograding %} #### Preventing changes to important files {% data reusables.classroom.assignments-guide-prevent-changes %} #### Creating a pull request for feedback {% data reusables.classroom.you-can-create-a-pull-request-for-feedback %} {% data reusables.classroom.assignments-guide-create-review-pull-request %} {% data reusables.classroom.assignments-guide-click-create-assignment-button %} ### Inviting students to an assignment {% data reusables.classroom.assignments-guide-invite-students-to-assignment %} You can see the teams that are working on or have submitted an assignment in the **Teams** tab for the assignment. {% data reusables.classroom.assignments-to-prevent-submission %} <div class="procedural-image-wrapper"> <img alt="Group assignment" class="procedural-image-wrapper" src="/assets/images/help/classroom/assignment-group-hero.png"> </div> ### Next steps - After you create the assignment and your students form teams, team members can start work on the assignment using Git and {% data variables.product.product_name %}'s features. Students can clone the repository, push commits, manage branches, create and review pull requests, address merge conflicts, and discuss changes with issues. Both you and the team can review the commit history for the repository. For more information, see "[Getting started with {% data variables.product.prodname_dotcom %}](/github/getting-started-with-github)," "[Creating, cloning, and archiving repositories](/github/creating-cloning-and-archiving-repositories)," "[Using Git](/github/using-git)," and "[Collaborating with issues and pull requests](/github/collaborating-with-issues-and-pull-requests)," and the free course on [managing merge conflicts](https://lab.github.com/githubtraining/managing-merge-conflicts) from {% data variables.product.prodname_learning %}. - When a team finishes an assignment, you can review the files in the repository, or you can review the history and visualizations for the repository to better understand how the team collaborated. For more information, see "[Visualizing repository data with graphs](/github/visualizing-repository-data-with-graphs)." - You can provide feedback for an assignment by commenting on individual commits or lines in a pull request. For more information, see "[Commenting on a pull request](/github/collaborating-with-issues-and-pull-requests/commenting-on-a-pull-request)" and "[Opening an issue from code](/github/managing-your-work-on-github/opening-an-issue-from-code)." For more information about creating saved replies to provide feedback for common errors, see "[About saved replies](/github/writing-on-github/about-saved-replies)." ### Further reading - "[Use {% data variables.product.prodname_dotcom %} in your classroom and research](/education/teach-and-learn-with-github-education/use-github-in-your-classroom-and-research)" - "[Connect a learning management system to {% data variables.product.prodname_classroom %}](/education/manage-coursework-with-github-classroom/connect-a-learning-management-system-to-github-classroom)" - [Using Existing Teams in Group Assignments?](https://education.github.community/t/using-existing-teams-in-group-assignments/6999) in the {% data variables.product.prodname_education %} Community 19 ...sework-with-github-classroom/create-an-assignment-from-a-template-repository.md @@ -0,0 +1,19 @@ --- title: Create an assignment from a template repository intro: You can create an assignment from a template repository to provide starter code, documentation, and other resources to your students. versions: free-pro-team: '*' redirect_from: - /education/manage-coursework-with-github-classroom/using-template-repos-for-assignments --- You can use a template repository on {% data variables.product.product_name %} as starter code for an assignment on {% data variables.product.prodname_classroom %}. Your template repository can contain boilerplate code, documentation, and other resources for your students. For more information, see "[Creating a template repository](/github/creating-cloning-and-archiving-repositories/creating-a-template-repository)." To use the template repository for your assignment, the template repository must be owned by your organization, or the visibility of the template repository must be public. {% data reusables.classroom.you-may-want-to-predefine-repository-settings %} For more information, see "[Configure default settings for assignment repositories](/education/manage-coursework-with-github-classroom/configure-default-settings-for-assignment-repositories)." ### Further reading - "[Create an individual assignment](/education/manage-coursework-with-github-classroom/create-an-individual-assignment)" - "[Create a group assignment](/education/manage-coursework-with-github-classroom/create-a-group-assignment)" 124 ...tion/manage-coursework-with-github-classroom/create-an-individual-assignment.md @@ -0,0 +1,124 @@ --- title: Create an individual assignment intro: You can create an assignment for students in your course to complete individually. versions: free-pro-team: '*' redirect_from: - /education/manage-coursework-with-github-classroom/creating-an-individual-assignment - /education/manage-coursework-with-github-classroom/create-an-individual-assignment --- ### About individual assignments {% data reusables.classroom.assignments-individual-definition %} {% data reusables.classroom.classroom-creates-individual-repositories %} {% data reusables.classroom.about-assignments %} For a video demonstration of the creation of an individual assignment, see "[Basics of setting up {% data variables.product.prodname_classroom %}](/education/manage-coursework-with-github-classroom/basics-of-setting-up-github-classroom)." ### Prerequisites {% data reusables.classroom.assignments-classroom-prerequisite %} ### Creating an assignment {% data reusables.classroom.assignments-guide-create-the-assignment %} ### Setting up the basics for an assignment Name your assignment, decide whether to assign a deadline, and choose the visibility of assignment repositories. - [Naming an assignment](#naming-an-assignment) - [Assigning a deadline for an assignment](#assigning-a-deadline-for-an-assignment) - [Choosing an assignment type](#choosing-an-assignment-type) - [Choosing a visibility for assignment repositories](#choosing-a-visibility-for-assignment-repositories) #### Naming an assignment For an individual assignment, {% data variables.product.prodname_classroom %} names repositories by the repository prefix and the student's {% data variables.product.product_name %} username. By default, the repository prefix is the assignment title. For example, if you name an assignment "assignment-1" and the student's username on {% data variables.product.product_name %} is @octocat, the name of the assignment repository for @octocat will be `assignment-1-octocat`. {% data reusables.classroom.assignments-type-a-title %} #### Assigning a deadline for an assignment {% data reusables.classroom.assignments-guide-assign-a-deadline %} #### Choosing an assignment type Under "Individual or group assignment", select the drop-down menu, and click **Individual assignment**. You can't change the assignment type after you create the assignment. If you'd rather create a group assignment, see "[Create a group assignment](/education/manage-coursework-with-github-classroom/create-a-group-assignment)." #### Choosing a visibility for assignment repositories {% data reusables.classroom.assignments-guide-choose-visibility %} {% data reusables.classroom.assignments-guide-click-continue-after-basics %} ### Adding starter code and configuring a development environment {% data reusables.classroom.assignments-guide-intro-for-environment %} - [Choosing a template repository](#choosing-a-template-repository) - [Choosing an online integrated development environment (IDE)](#choosing-an-online-integrated-development-environment-ide) #### Choosing a template repository By default, a new assignment will create an empty repository for each student on the roster for the classroom. {% data reusables.classroom.you-can-choose-a-template-repository %} For more information about template repositories, see "[Creating a template repository](/github/creating-cloning-and-archiving-repositories/creating-a-template-repository)." {% data reusables.classroom.assignments-guide-choose-template-repository %} {% data reusables.classroom.assignments-guide-click-continue-after-starter-code-and-feedback %} #### Choosing an online integrated development environment (IDE) {% data reusables.classroom.about-online-ides %} For more information, see "[Integrate {% data variables.product.prodname_classroom %} with an IDE](/education/manage-coursework-with-github-classroom/integrate-github-classroom-with-an-ide)." {% data reusables.classroom.assignments-guide-choose-an-online-ide %} ### Providing feedback for an assignment Optionally, you can automatically grade assignments and create a space for discussing each submission with the student. - [Testing assignments automatically](#testing-assignments-automatically) - [Preventing changes to important files](#preventing-changes-to-important-files) - [Creating a pull request for feedback](#creating-a-pull-request-for-feedback) #### Testing assignments automatically {% data reusables.classroom.assignments-guide-using-autograding %} #### Preventing changes to important files {% data reusables.classroom.assignments-guide-prevent-changes %} #### Creating a pull request for feedback {% data reusables.classroom.you-can-create-a-pull-request-for-feedback %} {% data reusables.classroom.assignments-guide-create-review-pull-request %} {% data reusables.classroom.assignments-guide-click-create-assignment-button %} ### Inviting students to an assignment {% data reusables.classroom.assignments-guide-invite-students-to-assignment %} You can see whether a student has joined the classroom and accepted or submitted an assignment in the **All students** tab for the assignment. {% data reusables.classroom.assignments-to-prevent-submission %} <div class="procedural-image-wrapper"> <img alt="Individual assignment" class="procedural-image-wrapper" src="/assets/images/help/classroom/assignment-individual-hero.png"> </div> ### Next steps - Once you create the assignment, students can start work on the assignment using Git and {% data variables.product.product_name %}'s features. Students can clone the repository, push commits, manage branches, create and review pull requests, address merge conflicts, and discuss changes with issues. Both you and student can review the commit history for the repository. For more information, see "[Getting started with {% data variables.product.prodname_dotcom %}](/github/getting-started-with-github)," "[Creating, cloning, and archiving repositories](/github/creating-cloning-and-archiving-repositories)," "[Using Git](/github/using-git)," and "[Collaborating with issues and pull requests](/github/collaborating-with-issues-and-pull-requests)." - When a student finishes an assignment, you can review the files in the repository, or you can review the history and visualizations for the repository to better understand the student's work. For more information, see "[Visualizing repository data with graphs](/github/visualizing-repository-data-with-graphs)." - You can provide feedback for an assignment by commenting on individual commits or lines in a pull request. For more information, see "[Commenting on a pull request](/github/collaborating-with-issues-and-pull-requests/commenting-on-a-pull-request)" and "[Opening an issue from code](/github/managing-your-work-on-github/opening-an-issue-from-code)." For more information about creating saved replies to provide feedback for common errors, see "[About saved replies](/github/writing-on-github/about-saved-replies)." ### Further reading - "[Use {% data variables.product.prodname_dotcom %} in your classroom and research](/education/teach-and-learn-with-github-education/use-github-in-your-classroom-and-research)" - "[Connect a learning management system to {% data variables.product.prodname_classroom %}](/education/manage-coursework-with-github-classroom/connect-a-learning-management-system-to-github-classroom)" 9 ...on/manage-coursework-with-github-classroom/get-started-with-github-classroom.md @@ -0,0 +1,9 @@ --- title: Get started with GitHub Classroom shortTitle: Get started intro: Learn how to configure and use {% data variables.product.prodname_classroom %} to administer your course. mapTopic: true versions: free-pro-team: '*' --- 52 content/education/manage-coursework-with-github-classroom/glossary.md @@ -0,0 +1,52 @@ --- title: Glossary intro: You can review explanations of terminology for {% data variables.product.prodname_classroom %}. versions: free-pro-team: '*' --- ### assignment An assignment is coursework in {% data variables.product.prodname_classroom %}. A teacher can assign an assignment to an individual student or a group of students. Teachers can import starter code for the assignment, assign students, and create a deadline for each assignment. For more information, see the definitions for "[individual assignment](#individual-assignment)" and "[group assignment](#group-assignment)." --- ### classroom A classroom is the basic unit of {% data variables.product.prodname_classroom %}. Teachers can use a classroom to organize and manage students, teaching assistants, and assignments for a single course. A classroom belongs to an organization on {% data variables.product.prodname_dotcom_the_website %}. To administer a classroom, you must be an organization owner for the organization on {% data variables.product.prodname_dotcom %}. For more information, see "[Manage classrooms](/education/manage-coursework-with-github-classroom/manage-classrooms)." --- ### {% data variables.product.prodname_classroom %} {% data variables.product.prodname_classroom %} is a web application for educators that provides course administration tools integrated with {% data variables.product.prodname_dotcom %}. For more information, see the [{% data variables.product.prodname_classroom %}](https://classroom.github.com/) website. --- ### group assignment {% data reusables.classroom.assignments-group-definition %} For more information, see "[Create a group assignment](/education/manage-coursework-with-github-classroom/create-a-group-assignment)." --- ### identifier An identifier in {% data variables.product.prodname_classroom %} is a unique ID for a student participating in a course. For example, an identifier can be a student name, alphanumeric ID, or email address. --- ### individual assignment {% data reusables.classroom.assignments-individual-definition %} For more information, see "[Create an individual assignment](/education/manage-coursework-with-github-classroom/create-an-individual-assignment)." --- ### roster A roster allows a teacher to manage students and assignment submissions in a classroom on {% data variables.product.prodname_classroom %}. Teachers can create a roster by entering a list of student identifiers, or by connecting {% data variables.product.prodname_classroom %} to a learning management system (LMS). For more information about identifiers, see the definition of "[identifier](#identifier)." For more information about connecting {% data variables.product.prodname_classroom %} to an LMS, see "[Connect a learning management system to {% data variables.product.prodname_classroom %}](/education/manage-coursework-with-github-classroom/connect-a-learning-management-system-to-github-classroom)." --- ### Further reading - "[{% data variables.product.prodname_dotcom %} glossary](/github/getting-started-with-github/github-glossary)" 32 content/education/manage-coursework-with-github-classroom/index.md @@ -0,0 +1,32 @@ --- title: Manage coursework with GitHub Classroom shortTitle: '{% data variables.product.prodname_classroom %}' intro: With {% data variables.product.prodname_classroom %}, you can use {% data variables.product.product_name %} to administer or participate in a course about software development. versions: free-pro-team: '*' --- ### Table of Contents {% topic_link_in_list /get-started-with-github-classroom %} {% link_in_list /basics-of-setting-up-github-classroom %} {% link_in_list /glossary %} {% topic_link_in_list /teach-with-github-classroom %} {% link_in_list /manage-classrooms %} {% link_in_list /create-an-individual-assignment %} {% link_in_list /create-a-group-assignment %} {% link_in_list /create-an-assignment-from-a-template-repository %} {% link_in_list /leave-feedback-with-pull-requests %} {% link_in_list /use-autograding %} {% link_in_list /configure-default-settings-for-assignment-repositories %} {% link_in_list /connect-a-learning-management-system-to-github-classroom %} {% topic_link_in_list /integrate-github-classroom-with-an-ide %} {% link_in_list /integrate-github-classroom-with-an-online-ide %} {% link_in_list /about-using-makecode-arcade-with-github-classroom %} {% link_in_list /about-using-replit-with-github-classroom %} {% link_in_list /run-student-code-in-an-online-ide %} {% topic_link_in_list /learn-with-github-classroom %} {% link_in_list /view-autograding-results %} 8 ...nage-coursework-with-github-classroom/integrate-github-classroom-with-an-ide.md @@ -0,0 +1,8 @@ --- title: Integrate GitHub Classroom with an IDE shortTitle: Integrate with an IDE intro: You can help your students write, test, and debug code by preconfiguring a development environment for assignment repositories on {% data variables.product.prodname_classroom %}. mapTopic: true versions: free-pro-team: '*' --- 42 ...ursework-with-github-classroom/integrate-github-classroom-with-an-online-ide.md @@ -0,0 +1,42 @@ --- title: Integrate GitHub Classroom with an online IDE shortTitle: Integrate with an online IDE intro: You can preconfigure a supported online integrated development environment (IDE) for assignments you create in {% data variables.product.prodname_classroom %}. versions: free-pro-team: '*' redirect_from: - /education/manage-coursework-with-github-classroom/online-ide-integrations --- ### About integration with an online IDE {% data reusables.classroom.about-online-ides %} After a student accepts an assignment with an online IDE, the README file in the student's assignment repository will contain a button to open the assignment in the IDE. The student can begin working immediately, and no additional configuration is necessary.  ### Supported online IDEs {% data variables.product.prodname_classroom %} supports the following online IDEs. You can learn more about the student experience for each IDE. | IDE | More information | | :- | :- | | Microsoft MakeCode Arcade | "[About using MakeCode Arcade with {% data variables.product.prodname_classroom %}](/education/manage-coursework-with-github-classroom/about-using-makecode-arcade-with-github-classroom)" | | Repl.it | "[About using Repl.it with GitHub Classroom](/education/manage-coursework-with-github-classroom/about-using-replit-with-github-classroom)" | ### Configuring an online IDE for an assignment You can choose the online IDE you'd like to use for an assignment when you create an assignment. To learn how to create a new assignment that uses an online IDE, see "[Create an individual assignment](/education/manage-coursework-with-github-classroom/create-an-individual-assignment)" or "[Create a group assignment](/education/manage-coursework-with-github-classroom/create-a-group-assignment)." ### Authorizing the OAuth app for an online IDE The first time you configure an assignment with an online IDE, you must authorize the OAuth app for the online IDE for your organization.  For all repositories, grant the app **read** access to metadata, administration, and code, and **write** access to administration and code. For more information, see "[Authorizing OAuth Apps](/github/authenticating-to-github/authorizing-oauth-apps)." ### Further reading - "[About READMEs](/github/creating-cloning-and-archiving-repositories/about-readmes)" 7 ...ducation/manage-coursework-with-github-classroom/learn-with-github-classroom.md @@ -0,0 +1,7 @@ --- title: Learn with GitHub Classroom intro: You can participate in coursework in {% data variables.product.prodname_classroom %} and see results from your teacher. mapTopic: true versions: free-pro-team: '*' --- 33 ...on/manage-coursework-with-github-classroom/leave-feedback-with-pull-requests.md @@ -0,0 +1,33 @@ --- title: Leave feedback with pull requests intro: You can leave feedback for your students in a special pull request within the repository for each assignment. permissions: People with read permissions to a repository can leave feedback in a pull request for the repository. versions: free-pro-team: '*' redirect_from: - /education/manage-coursework-with-github-classroom/leaving-feedback-in-github --- ### About feedback pull requests for assignments {% data reusables.classroom.you-can-create-a-pull-request-for-feedback %} When you enable the pull request for feedback for an assignment, {% data variables.product.prodname_classroom %} will create a special pull request titled **Feedback** in the assignment repository for each student or team. The pull request automatically shows every commit that a student pushed to the assignment repository's default branch. ### Prerequisites To create and access the feedback pull request, you must enable the feedback pull request when you create the assignment. {% data reusables.classroom.for-more-information-about-assignment-creation %} ### Leaving feedback in a pull request for an assignment {% data reusables.classroom.sign-into-github-classroom %} 1. In the list of classrooms, click the classroom with the assignment you want to review.  {% data reusables.classroom.click-assignment-in-list %} 1. To the right of the submission, click **Review**.  1. Review the pull request. For more information, see "[Commenting on a pull request](/github/collaborating-with-issues-and-pull-requests/commenting-on-a-pull-request)." ### Further reading - "[Integrate {% data variables.product.prodname_classroom %} with an IDE](http://localhost:4000/en/free-pro-team@latest/education/manage-coursework-with-github-classroom/integrate-github-classroom-with-an-ide)" 121 content/education/manage-coursework-with-github-classroom/manage-classrooms.md @@ -0,0 +1,121 @@ --- title: Manage classrooms intro: You can create and manage a classroom for each course that you teach using {% data variables.product.prodname_classroom %}. permissions: Organization owners can manage a classroom for an organization. versions: free-pro-team: '*' redirect_from: - /education/manage-coursework-with-github-classroom/archive-a-classroom --- ### About classrooms {% data reusables.classroom.about-classrooms %}  ### About management of classrooms {% data variables.product.prodname_classroom %} uses organization accounts on {% data variables.product.product_name %} to manage permissions, administration, and security for each classroom that you create. Each organization can have multiple classrooms. After you create a classroom, {% data variables.product.prodname_classroom %} will prompt you to invite teaching assistants (TAs) and admins to the classroom. Each classroom can have one or more admins. Admins can be teachers, TAs, or any other course administrator who you'd like to have control over your classrooms on {% data variables.product.prodname_classroom %}. Invite TAs and admins to your classroom by inviting the user accounts on {% data variables.product.product_name %} to your organization as organization owners and sharing the URL for your classrom. Organization owners can administer any classroom for the organization. For more information, see "[Permission levels for an organization](/github/setting-up-and-managing-organizations-and-teams/permission-levels-for-an-organization)" and "[Inviting users to join your organization](/github/setting-up-and-managing-organizations-and-teams/inviting-users-to-join-your-organization)." When you're done using a classroom, you can archive the classroom and refer to the classroom, roster, and assignments later, or you can delete the classroom if you no longer need the classroom. ### About classroom rosters Each classroom has a roster. A roster is a list of identifiers for the students who participate in your course. When you first share the URL for an assignment with a student, the student must sign into {% data variables.product.product_name %} with a user account to link the user account to an identifier for the classroom. After the student links a user account, you can see the associated user account in the roster. You can also see when the student accepts or submits an assignment.  ### Prerequisites You must have an organization account on {% data variables.product.product_name %} to manage classrooms on {% data variables.product.prodname_classroom %}. For more information, see "[Types of {% data variables.product.company_short %} accounts](/github/getting-started-with-github/types-of-github-accounts#organization-accounts)" and "[Creating a new organization from scratch](/github/setting-up-and-managing-organizations-and-teams/creating-a-new-organization-from-scratch)." You must authorize the OAuth app for {% data variables.product.prodname_classroom %} for your organization to manage classrooms for your organization account. For more information, see "[Authorizing OAuth Apps](/github/authenticating-to-github/authorizing-oauth-apps)." ### Creating a classroom {% data reusables.classroom.sign-into-github-classroom %} 1. Click **New classroom**.  {% data reusables.classroom.guide-create-new-classroom %} After you create a classroom, you can begin creating assignments for students. For more information, see "[Create an individual assignment](/education/manage-coursework-with-github-classroom/create-an-individual-assignment)" or "[Create a group assignment](/education/manage-coursework-with-github-classroom/create-a-group-assignment)." ### Creating a roster for your classroom You can create a roster of the students who participate in your course. If your course already has a roster, you can update the students on the roster or delete the roster. For more information, see "[Adding a student to the roster for your classroom](#adding-students-to-the-roster-for-your-classroom)" or "[Deleting a roster for a classroom](#deleting-a-roster-for-a-classroom)." {% data reusables.classroom.sign-into-github-classroom %} {% data reusables.classroom.click-classroom-in-list %} {% data reusables.classroom.click-students %} 1. To connect {% data variables.product.prodname_classroom %} to your LMS and import a roster, click {% octicon "mortar-board" aria-label="The mortar board icon" %} **Import from a learning management system** and follow the instructions. For more information, see "[Connect a learning management system to {% data variables.product.prodname_classroom %}](/education/manage-coursework-with-github-classroom/connect-a-learning-management-system-to-github-classroom)."  1. To create a roster manually, type your student identifiers. Optionally, click **Upload a CSV or text file** to upload a file containing the identifiers.  1. Click **Create roster**.  ### Adding students to the roster for your classroom Your classroom must have an existing roster to add students to the roster. For more information about creating a roster, see "[Creating a roster for your classrom](#creating-a-roster-for-your-classroom)." {% data reusables.classroom.sign-into-github-classroom %} {% data reusables.classroom.click-classroom-in-list %} {% data reusables.classroom.click-students %} 1. To the right of "Classroom roster", click **Update students**.  1. Follow the instructions to add students to the roster. - To import students from an LMS, click **Sync from a learning management system**. For more information about importing a roster from an LMS, see "[Connect a learning management system to {% data variables.product.prodname_classroom %}](/education/manage-coursework-with-github-classroom/connect-a-learning-management-system-to-github-classroom)." - To manually add students, under "Manually add students", click **Upload a CSV or text file** or type the identifiers for the students, then click **Add roster entries**.  ### Renaming a classroom {% data reusables.classroom.sign-into-github-classroom %} {% data reusables.classroom.click-classroom-in-list %} {% data reusables.classroom.click-settings %} 1. Under "Classroom name", type a new name for the classroom.  1. Click **Rename classroom**.  ### Archiving or unarchiving a classroom You can archive a classroom that you no longer use on {% data variables.product.prodname_classroom %}. When you archive a classroom, you can't create new assignments or edit existing assignments for the classroom. Students can't accept invitations to assignments in archived classrooms. {% data reusables.classroom.sign-into-github-classroom %} 1. To the right of a classroom's name, select the {% octicon "kebab-horizontal" aria-label="The horizontal kebab icon" %} drop-down menu, then click **Archive**.  1. To unarchive a classroom, to the right of a classroom's name, select the {% octicon "kebab-horizontal" aria-label="The horizontal kebab icon" %} drop-down menu, then click **Unarchive**.  ### Deleting a roster for a classroom {% data reusables.classroom.sign-into-github-classroom %} {% data reusables.classroom.click-classroom-in-list %} {% data reusables.classroom.click-students %} 1. Under "Delete this roster", click **Delete roster**.  1. Read the warnings, then click **Delete roster**.  ### Deleting a classroom {% data reusables.classroom.sign-into-github-classroom %} {% data reusables.classroom.click-classroom-in-list %} {% data reusables.classroom.click-settings %} 1. To the right of "Delete this classroom", click **Delete classroom**.  1. **Read the warnings**. 1. To verify that you're deleting the correct classroom, type the name of the classroom you want to delete.  1. Click **Delete classroom**.  22 ...on/manage-coursework-with-github-classroom/run-student-code-in-an-online-ide.md @@ -0,0 +1,22 @@ --- title: Run student code in an online IDE intro: You can run the code from a student assignment within the online integrated development environment (IDE) that you configured for the assignment. versions: free-pro-team: '*' redirect_from: - /education/manage-coursework-with-github-classroom/running-student-code --- ### About student code and online IDEs If you configure an online integrated development environment (IDE) for an assignment, you can run the code within the online IDE. You don't need to clone the assignment repository to your computer. For more information about online IDEs, see "[Integrate {% data variables.product.prodname_classroom %} with an online IDE](/education/manage-coursework-with-github-classroom/integrate-github-classroom-with-an-online-ide)." ### Running student code in the online IDE {% data reusables.classroom.sign-into-github-classroom %} {% data reusables.classroom.click-classroom-in-list %} {% data reusables.classroom.click-assignment-in-list %} 1. To the right of the submission, click **View IDE**.  8 ...ducation/manage-coursework-with-github-classroom/teach-with-github-classroom.md @@ -0,0 +1,8 @@ --- title: Teach with GitHub Classroom intro: Learn how to set up your classroom and assignments. mapTopic: true versions: free-pro-team: '*' --- 93 content/education/manage-coursework-with-github-classroom/use-autograding.md 30 ...t/education/manage-coursework-with-github-classroom/view-autograding-results.md 90 content/education/quickstart.md 1 ...github-education/about-campus-advisors.md → ...github-education/about-campus-advisors.md 1 ...-github-education/about-campus-experts.md → ...-github-education/about-campus-experts.md 1 ...ducation-for-educators-and-researchers.md → ...ducation-for-educators-and-researchers.md 5 ...on/about-github-education-for-students.md → ...on/about-github-education-for-students.md 9 ...ithub-education/about-github-education.md → ...ithub-education/about-github-education.md 5 .../applying-for-a-student-developer-pack.md → ...ion/apply-for-a-student-developer-pack.md 14 ...for-an-educator-or-researcher-discount.md → ...for-an-educator-or-researcher-discount.md 26 content/education/teach-and-learn-with-github-education/index.md 3 ...github-at-your-educational-institution.md → ...github-at-your-educational-institution.md 3 ...ation/using-github-for-your-schoolwork.md → ...ucation/use-github-for-your-schoolwork.md 3 ...-github-in-your-classroom-and-research.md → ...-github-in-your-classroom-and-research.md 5 ...-for-a-student-developer-pack-approved.md → ...-for-a-student-developer-pack-approved.md 3 ...ucator-or-researcher-discount-approved.md → ...ucator-or-researcher-discount-approved.md 20 ...ering-a-repository/enabling-or-disabling-github-discussions-for-a-repository.md 5 content/github/administering-a-repository/index.md 2 content/github/authenticating-to-github/reviewing-your-security-log.md 1 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PramuPerera / DeepOneClassDeep learning based one class classification code targeting one class image classification. Tests carried out on Abnormal image detection, Novel image detection and Active Authentication reported state of the art results.
Aastha2104 / Parkinson Disease PredictionIntroduction Parkinson’s Disease is the second most prevalent neurodegenerative disorder after Alzheimer’s, affecting more than 10 million people worldwide. Parkinson’s is characterized primarily by the deterioration of motor and cognitive ability. There is no single test which can be administered for diagnosis. Instead, doctors must perform a careful clinical analysis of the patient’s medical history. Unfortunately, this method of diagnosis is highly inaccurate. A study from the National Institute of Neurological Disorders finds that early diagnosis (having symptoms for 5 years or less) is only 53% accurate. This is not much better than random guessing, but an early diagnosis is critical to effective treatment. Because of these difficulties, I investigate a machine learning approach to accurately diagnose Parkinson’s, using a dataset of various speech features (a non-invasive yet characteristic tool) from the University of Oxford. Why speech features? Speech is very predictive and characteristic of Parkinson’s disease; almost every Parkinson’s patient experiences severe vocal degradation (inability to produce sustained phonations, tremor, hoarseness), so it makes sense to use voice to diagnose the disease. Voice analysis gives the added benefit of being non-invasive, inexpensive, and very easy to extract clinically. Background Parkinson's Disease Parkinson’s is a progressive neurodegenerative condition resulting from the death of the dopamine containing cells of the substantia nigra (which plays an important role in movement). Symptoms include: “frozen” facial features, bradykinesia (slowness of movement), akinesia (impairment of voluntary movement), tremor, and voice impairment. Typically, by the time the disease is diagnosed, 60% of nigrostriatal neurons have degenerated, and 80% of striatal dopamine have been depleted. Performance Metrics TP = true positive, FP = false positive, TN = true negative, FN = false negative Accuracy: (TP+TN)/(P+N) Matthews Correlation Coefficient: 1=perfect, 0=random, -1=completely inaccurate Algorithms Employed Logistic Regression (LR): Uses the sigmoid logistic equation with weights (coefficient values) and biases (constants) to model the probability of a certain class for binary classification. An output of 1 represents one class, and an output of 0 represents the other. Training the model will learn the optimal weights and biases. Linear Discriminant Analysis (LDA): Assumes that the data is Gaussian and each feature has the same variance. LDA estimates the mean and variance for each class from the training data, and then uses properties of statistics (Bayes theorem , Gaussian distribution, etc) to compute the probability of a particular instance belonging to a given class. The class with the largest probability is the prediction. k Nearest Neighbors (KNN): Makes predictions about the validation set using the entire training set. KNN makes a prediction about a new instance by searching through the entire set to find the k “closest” instances. “Closeness” is determined using a proximity measurement (Euclidean) across all features. The class that the majority of the k closest instances belong to is the class that the model predicts the new instance to be. Decision Tree (DT): Represented by a binary tree, where each root node represents an input variable and a split point, and each leaf node contains an output used to make a prediction. Neural Network (NN): Models the way the human brain makes decisions. Each neuron takes in 1+ inputs, and then uses an activation function to process the input with weights and biases to produce an output. Neurons can be arranged into layers, and multiple layers can form a network to model complex decisions. Training the network involves using the training instances to optimize the weights and biases. Naive Bayes (NB): Simplifies the calculation of probabilities by assuming that all features are independent of one another (a strong but effective assumption). Employs Bayes Theorem to calculate the probabilities that the instance to be predicted is in each class, then finds the class with the highest probability. Gradient Boost (GB): Generally used when seeking a model with very high predictive performance. Used to reduce bias and variance (“error”) by combining multiple “weak learners” (not very good models) to create a “strong learner” (high performance model). Involves 3 elements: a loss function (error function) to be optimized, a weak learner (decision tree) to make predictions, and an additive model to add trees to minimize the loss function. Gradient descent is used to minimize error after adding each tree (one by one). Engineering Goal Produce a machine learning model to diagnose Parkinson’s disease given various features of a patient’s speech with at least 90% accuracy and/or a Matthews Correlation Coefficient of at least 0.9. Compare various algorithms and parameters to determine the best model for predicting Parkinson’s. Dataset Description Source: the University of Oxford 195 instances (147 subjects with Parkinson’s, 48 without Parkinson’s) 22 features (elements that are possibly characteristic of Parkinson’s, such as frequency, pitch, amplitude / period of the sound wave) 1 label (1 for Parkinson’s, 0 for no Parkinson’s) Project Pipeline pipeline Summary of Procedure Split the Oxford Parkinson’s Dataset into two parts: one for training, one for validation (evaluate how well the model performs) Train each of the following algorithms with the training set: Logistic Regression, Linear Discriminant Analysis, k Nearest Neighbors, Decision Tree, Neural Network, Naive Bayes, Gradient Boost Evaluate results using the validation set Repeat for the following training set to validation set splits: 80% training / 20% validation, 75% / 25%, and 70% / 30% Repeat for a rescaled version of the dataset (scale all the numbers in the dataset to a range from 0 to 1: this helps to reduce the effect of outliers) Conduct 5 trials and average the results Data a_o a_r m_o m_r Data Analysis In general, the models tended to perform the best (both in terms of accuracy and Matthews Correlation Coefficient) on the rescaled dataset with a 75-25 train-test split. The two highest performing algorithms, k Nearest Neighbors and the Neural Network, both achieved an accuracy of 98%. The NN achieved a MCC of 0.96, while KNN achieved a MCC of 0.94. These figures outperform most existing literature and significantly outperform current methods of diagnosis. Conclusion and Significance These robust results suggest that a machine learning approach can indeed be implemented to significantly improve diagnosis methods of Parkinson’s disease. Given the necessity of early diagnosis for effective treatment, my machine learning models provide a very promising alternative to the current, rather ineffective method of diagnosis. Current methods of early diagnosis are only 53% accurate, while my machine learning model produces 98% accuracy. This 45% increase is critical because an accurate, early diagnosis is needed to effectively treat the disease. Typically, by the time the disease is diagnosed, 60% of nigrostriatal neurons have degenerated, and 80% of striatal dopamine have been depleted. With an earlier diagnosis, much of this degradation could have been slowed or treated. My results are very significant because Parkinson’s affects over 10 million people worldwide who could benefit greatly from an early, accurate diagnosis. Not only is my machine learning approach more accurate in terms of diagnostic accuracy, it is also more scalable, less expensive, and therefore more accessible to people who might not have access to established medical facilities and professionals. The diagnosis is also much simpler, requiring only a 10-15 second voice recording and producing an immediate diagnosis. Future Research Given more time and resources, I would investigate the following: Create a mobile application which would allow the user to record his/her voice, extract the necessary vocal features, and feed it into my machine learning model to diagnose Parkinson’s. Use larger datasets in conjunction with the University of Oxford dataset. Tune and improve my models even further to achieve even better results. Investigate different structures and types of neural networks. Construct a novel algorithm specifically suited for the prediction of Parkinson’s. Generalize my findings and algorithms for all types of dementia disorders, such as Alzheimer’s. References Bind, Shubham. "A Survey of Machine Learning Based Approaches for Parkinson Disease Prediction." International Journal of Computer Science and Information Technologies 6 (2015): n. pag. International Journal of Computer Science and Information Technologies. 2015. Web. 8 Mar. 2017. Brooks, Megan. "Diagnosing Parkinson's Disease Still Challenging." Medscape Medical News. National Institute of Neurological Disorders, 31 July 2014. Web. 20 Mar. 2017. Exploiting Nonlinear Recurrence and Fractal Scaling Properties for Voice Disorder Detection', Little MA, McSharry PE, Roberts SJ, Costello DAE, Moroz IM. BioMedical Engineering OnLine 2007, 6:23 (26 June 2007) Hashmi, Sumaiya F. "A Machine Learning Approach to Diagnosis of Parkinson’s Disease."Claremont Colleges Scholarship. Claremont College, 2013. Web. 10 Mar. 2017. Karplus, Abraham. "Machine Learning Algorithms for Cancer Diagnosis." Machine Learning Algorithms for Cancer Diagnosis (n.d.): n. pag. Mar. 2012. Web. 20 Mar. 2017. Little, Max. "Parkinsons Data Set." UCI Machine Learning Repository. University of Oxford, 26 June 2008. Web. 20 Feb. 2017. Ozcift, Akin, and Arif Gulten. "Classifier Ensemble Construction with Rotation Forest to Improve Medical Diagnosis Performance of Machine Learning Algorithms." Computer Methods and Programs in Biomedicine 104.3 (2011): 443-51. Semantic Scholar. 2011. Web. 15 Mar. 2017. "Parkinson’s Disease Dementia." UCI MIND. N.p., 19 Oct. 2015. Web. 17 Feb. 2017. Salvatore, C., A. Cerasa, I. Castiglioni, F. Gallivanone, A. Augimeri, M. Lopez, G. Arabia, M. Morelli, M.c. Gilardi, and A. Quattrone. "Machine Learning on Brain MRI Data for Differential Diagnosis of Parkinson's Disease and Progressive Supranuclear Palsy."Journal of Neuroscience Methods 222 (2014): 230-37. 2014. Web. 18 Mar. 2017. Shahbakhi, Mohammad, Danial Taheri Far, and Ehsan Tahami. "Speech Analysis for Diagnosis of Parkinson’s Disease Using Genetic Algorithm and Support Vector Machine."Journal of Biomedical Science and Engineering 07.04 (2014): 147-56. Scientific Research. July 2014. Web. 2 Mar. 2017. "Speech and Communication." Speech and Communication. Parkinson's Disease Foundation, n.d. Web. 22 Mar. 2017. Sriram, Tarigoppula V. S., M. Venkateswara Rao, G. V. Satya Narayana, and D. S. V. G. K. Kaladhar. "Diagnosis of Parkinson Disease Using Machine Learning and Data Mining Systems from Voice Dataset." SpringerLink. Springer, Cham, 01 Jan. 1970. Web. 17 Mar. 2017.
himanshub1007 / Alzhimers Disease Prediction Using Deep Learning# AD-Prediction Convolutional Neural Networks for Alzheimer's Disease Prediction Using Brain MRI Image ## Abstract Alzheimers disease (AD) is characterized by severe memory loss and cognitive impairment. It associates with significant brain structure changes, which can be measured by magnetic resonance imaging (MRI) scan. The observable preclinical structure changes provides an opportunity for AD early detection using image classification tools, like convolutional neural network (CNN). However, currently most AD related studies were limited by sample size. Finding an efficient way to train image classifier on limited data is critical. In our project, we explored different transfer-learning methods based on CNN for AD prediction brain structure MRI image. We find that both pretrained 2D AlexNet with 2D-representation method and simple neural network with pretrained 3D autoencoder improved the prediction performance comparing to a deep CNN trained from scratch. The pretrained 2D AlexNet performed even better (**86%**) than the 3D CNN with autoencoder (**77%**). ## Method #### 1. Data In this project, we used public brain MRI data from **Alzheimers Disease Neuroimaging Initiative (ADNI)** Study. ADNI is an ongoing, multicenter cohort study, started from 2004. It focuses on understanding the diagnostic and predictive value of Alzheimers disease specific biomarkers. The ADNI study has three phases: ADNI1, ADNI-GO, and ADNI2. Both ADNI1 and ADNI2 recruited new AD patients and normal control as research participants. Our data included a total of 686 structure MRI scans from both ADNI1 and ADNI2 phases, with 310 AD cases and 376 normal controls. We randomly derived the total sample into training dataset (n = 519), validation dataset (n = 100), and testing dataset (n = 67). #### 2. Image preprocessing Image preprocessing were conducted using Statistical Parametric Mapping (SPM) software, version 12. The original MRI scans were first skull-stripped and segmented using segmentation algorithm based on 6-tissue probability mapping and then normalized to the International Consortium for Brain Mapping template of European brains using affine registration. Other configuration includes: bias, noise, and global intensity normalization. The standard preprocessing process output 3D image files with an uniform size of 121x145x121. Skull-stripping and normalization ensured the comparability between images by transforming the original brain image into a standard image space, so that same brain substructures can be aligned at same image coordinates for different participants. Diluted or enhanced intensity was used to compensate the structure changes. the In our project, we used both whole brain (including both grey matter and white matter) and grey matter only. #### 3. AlexNet and Transfer Learning Convolutional Neural Networks (CNN) are very similar to ordinary Neural Networks. A CNN consists of an input and an output layer, as well as multiple hidden layers. The hidden layers are either convolutional, pooling or fully connected. ConvNet architectures make the explicit assumption that the inputs are images, which allows us to encode certain properties into the architecture. These then make the forward function more efficient to implement and vastly reduce the amount of parameters in the network. #### 3.1. AlexNet The net contains eight layers with weights; the first five are convolutional and the remaining three are fully connected. The overall architecture is shown in Figure 1. The output of the last fully-connected layer is fed to a 1000-way softmax which produces a distribution over the 1000 class labels. AlexNet maximizes the multinomial logistic regression objective, which is equivalent to maximizing the average across training cases of the log-probability of the correct label under the prediction distribution. The kernels of the second, fourth, and fifth convolutional layers are connected only to those kernel maps in the previous layer which reside on the same GPU (as shown in Figure1). The kernels of the third convolutional layer are connected to all kernel maps in the second layer. The neurons in the fully connected layers are connected to all neurons in the previous layer. Response-normalization layers follow the first and second convolutional layers. Max-pooling layers follow both response-normalization layers as well as the fifth convolutional layer. The ReLU non-linearity is applied to the output of every convolutional and fully-connected layer.  The first convolutional layer filters the 224x224x3 input image with 96 kernels of size 11x11x3 with a stride of 4 pixels (this is the distance between the receptive field centers of neighboring neurons in a kernel map). The second convolutional layer takes as input the (response-normalized and pooled) output of the first convolutional layer and filters it with 256 kernels of size 5x5x48. The third, fourth, and fifth convolutional layers are connected to one another without any intervening pooling or normalization layers. The third convolutional layer has 384 kernels of size 3x3x256 connected to the (normalized, pooled) outputs of the second convolutional layer. The fourth convolutional layer has 384 kernels of size 3x3x192 , and the fifth convolutional layer has 256 kernels of size 3x3x192. The fully-connected layers have 4096 neurons each. #### 3.2. Transfer Learning Training an entire Convolutional Network from scratch (with random initialization) is impractical[14] because it is relatively rare to have a dataset of sufficient size. An alternative is to pretrain a Conv-Net on a very large dataset (e.g. ImageNet), and then use the ConvNet either as an initialization or a fixed feature extractor for the task of interest. Typically, there are three major transfer learning scenarios: **ConvNet as fixed feature extractor:** We can take a ConvNet pretrained on ImageNet, and remove the last fully-connected layer, then treat the rest structure as a fixed feature extractor for the target dataset. In AlexNet, this would be a 4096-D vector. Usually, we call these features as CNN codes. Once we get these features, we can train a linear classifier (e.g. linear SVM or Softmax classifier) for our target dataset. **Fine-tuning the ConvNet:** Another idea is not only replace the last fully-connected layer in the classifier, but to also fine-tune the parameters of the pretrained network. Due to overfitting concerns, we can only fine-tune some higher-level part of the network. This suggestion is motivated by the observation that earlier features in a ConvNet contains more generic features (e.g. edge detectors or color blob detectors) that can be useful for many kind of tasks. But the later layer of the network becomes progressively more specific to the details of the classes contained in the original dataset. **Pretrained models:** The released pretrained model is usually the final ConvNet checkpoint. So it is common to see people use the network for fine-tuning. #### 4. 3D Autoencoder and Convolutional Neural Network We take a two-stage approach where we first train a 3D sparse autoencoder to learn filters for convolution operations, and then build a convolutional neural network whose first layer uses the filters learned with the autoencoder.  #### 4.1. Sparse Autoencoder An autoencoder is a 3-layer neural network that is used to extract features from an input such as an image. Sparse representations can provide a simple interpretation of the input data in terms of a small number of \parts by extracting the structure hidden in the data. The autoencoder has an input layer, a hidden layer and an output layer, and the input and output layers have same number of units, while the hidden layer contains more units for a sparse and overcomplete representation. The encoder function maps input x to representation h, and the decoder function maps the representation h to the output x. In our problem, we extract 3D patches from scans as the input to the network. The decoder function aims to reconstruct the input form the hidden representation h. #### 4.2. 3D Convolutional Neural Network Training the 3D convolutional neural network(CNN) is the second stage. The CNN we use in this project has one convolutional layer, one pooling layer, two linear layers, and finally a log softmax layer. After training the sparse autoencoder, we take the weights and biases of the encoder from trained model, and use them a 3D filter of a 3D convolutional layer of the 1-layer convolutional neural network. Figure 2 shows the architecture of the network. #### 5. Tools In this project, we used Nibabel for MRI image processing and PyTorch Neural Networks implementation.
jettbrains / L W3C Strategic Highlights September 2019 This report was prepared for the September 2019 W3C Advisory Committee Meeting (W3C Member link). See the accompanying W3C Fact Sheet — September 2019. For the previous edition, see the April 2019 W3C Strategic Highlights. For future editions of this report, please consult the latest version. A Chinese translation is available. ☰ Contents Introduction Future Web Standards Meeting Industry Needs Web Payments Digital Publishing Media and Entertainment Web & Telecommunications Real-Time Communications (WebRTC) Web & Networks Automotive Web of Things Strengthening the Core of the Web HTML CSS Fonts SVG Audio Performance Web Performance WebAssembly Testing Browser Testing and Tools WebPlatform Tests Web of Data Web for All Security, Privacy, Identity Internationalization (i18n) Web Accessibility Outreach to the world W3C Developer Relations W3C Training Translations W3C Liaisons Introduction This report highlights recent work of enhancement of the existing landscape of the Web platform and innovation for the growth and strength of the Web. 33 working groups and a dozen interest groups enable W3C to pursue its mission through the creation of Web standards, guidelines, and supporting materials. We track the tremendous work done across the Consortium through homogeneous work-spaces in Github which enables better monitoring and management. We are in the middle of a period where we are chartering numerous working groups which demonstrate the rapid degree of change for the Web platform: After 4 years, we are nearly ready to publish a Payment Request API Proposed Recommendation and we need to soon charter follow-on work. In the last year we chartered the Web Payment Security Interest Group. In the last year we chartered the Web Media Working Group with 7 specifications for next generation Media support on the Web. We have Accessibility Guidelines under W3C Member review which includes Silver, a new approach. We have just launched the Decentralized Identifier Working Group which has tremendous potential because Decentralized Identifier (DID) is an identifier that is globally unique, resolveable with high availability, and cryptographically verifiable. We have Privacy IG (PING) under W3C Member review which strengthens our focus on the tradeoff between privacy and function. We have a new CSS charter under W3C Member review which maps the group's work for the next three years. In this period, W3C and the WHATWG have succesfully completed the negotiation of a Memorandum of Understanding rooted in the mutual belief that that having two distinct specifications claiming to be normative is generally harmful for the Web community. The MOU, signed last May, describes how the two organizations are to collaborate on the development of a single authoritative version of the HTML and DOM specifications. W3C subsequently rechartered the HTML Working Group to assist the W3C community in raising issues and proposing solutions for the HTML and DOM specifications, and for the production of W3C Recommendations from WHATWG Review Drafts. As the Web evolves continuously, some groups are looking for ways for specifications to do so as well. So-called "evergreen recommendations" or "living standards" aim to track continuous development (and maintenance) of features, on a feature-by-feature basis, while getting review and patent commitments. We see the maturation and further development of an incredible number of new technologies coming to the Web. Continued progress in many areas demonstrates the vitality of the W3C and the Web community, as the rest of the report illustrates. Future Web Standards W3C has a variety of mechanisms for listening to what the community thinks could become good future Web standards. These include discussions with the Membership, discussions with other standards bodies, the activities of thousands of participants in over 300 community groups, and W3C Workshops. There are lots of good ideas. The W3C strategy team has been identifying promising topics and invites public participation. Future, recent and under consideration Workshops include: Inclusive XR (5-6 November 2019, Seattle, WA, USA) to explore existing and future approaches on making Virtual and Augmented Reality experiences more inclusive, including to people with disabilities; W3C Workshop on Data Models for Transportation (12-13 September 2019, Palo Alto, CA, USA) W3C Workshop on Web Games (27-28 June 2019, Redmond, WA, USA), view report Second W3C Workshop on the Web of Things (3-5 June 2019, Munich, Germany) W3C Workshop on Web Standardization for Graph Data; Creating Bridges: RDF, Property Graph and SQL (4-6 March 2019, Berlin, Germany), view report Web & Machine Learning. The Strategy Funnel documents the staff's exploration of potential new work at various phases: Exploration and Investigation, Incubation and Evaluation, and eventually to the chartering of a new standards group. The Funnel view is a GitHub Project where new area are issues represented by “cards” which move through the columns, usually from left to right. Most cards start in Exploration and move towards Chartering, or move out of the funnel. Public input is welcome at any stage but particularly once Incubation has begun. This helps W3C identify work that is sufficiently incubated to warrant standardization, to review the ecosystem around the work and indicate interest in participating in its standardization, and then to draft a charter that reflects an appropriate scope. Ongoing feedback can speed up the overall standardization process. Since the previous highlights document, W3C has chartered a number of groups, and started discussion on many more: Newly Chartered or Rechartered Web Application Security WG (03-Apr) Web Payment Security IG (17-Apr) Patent and Standards IG (24-Apr) Web Applications WG (14-May) Web & Networks IG (16-May) Media WG (23-May) Media and Entertainment IG (06-Jun) HTML WG (06-Jun) Decentralized Identifier WG (05-Sep) Extended Privacy IG (PING) (30-Sep) Verifiable Claims WG (30-Sep) Service Workers WG (31-Dec) Dataset Exchange WG (31-Dec) Web of Things Working Group (31-Dec) Web Audio Working Group (31-Dec) Proposed charters / Advance Notice Accessibility Guidelines WG Privacy IG (PING) RDF Literal Direction WG Timed Text WG CSS WG Web Authentication WG Closed Internationalization Tag Set IG Meeting Industry Needs Web Payments All Web Payments specifications W3C's payments standards enable a streamlined checkout experience, enabling a consistent user experience across the Web with lower front end development costs for merchants. Users can store and reuse information and more quickly and accurately complete online transactions. The Web Payments Working Group has republished Payment Request API as a Candidate Recommendation, aiming to publish a Proposed Recommendation in the Fall 2019, and is discussing use cases and features for Payment Request after publication of the 1.0 Recommendation. Browser vendors have been finalizing implementation of features added in the past year (view the implementation report). As work continues on the Payment Handler API and its implementation (currently in Chrome and Edge Canary), one focus in 2019 is to increase adoption in other browsers. Recently, Mastercard demonstrated the use of Payment Request API to carry out EMVCo's Secure Remote Commerce (SRC) protocol whose payment method definition is being developed with active participation by Visa, Mastercard, American Express, and Discover. Payment method availability is a key factor in merchant considerations about adopting Payment Request API. The ability to get uniform adoption of a new payment method such as Secure Remote Commerce (SRC) also depends on the availability of the Payment Handler API in browsers, or of proprietary alternatives. Web Monetization, which the Web Payments Working Group will discuss again at its face-to-face meeting in September, can be used to enable micropayments as an alternative revenue stream to advertising. Since the beginning of 2019, Amazon, Brave Software, JCB, Certus Cybersecurity Solutions and Netflix have joined the Web Payments Working Group. In April, W3C launched the Web Payment Security Group to enable W3C, EMVCo, and the FIDO Alliance to collaborate on a vision for Web payment security and interoperability. Participants will define areas of collaboration and identify gaps between existing technical specifications in order to increase compatibility among different technologies, such as: How do SRC, FIDO, and Payment Request relate? The Payment Services Directive 2 (PSD2) regulations in Europe are scheduled to take effect in September 2019. What is the role of EMVCo, W3C, and FIDO technologies, and what is the current state of readiness for the deadline? How can we improve privacy on the Web at the same time as we meet industry requirements regarding user identity? Digital Publishing All Digital Publishing specifications, Publication milestones The Web is the universal publishing platform. Publishing is increasingly impacted by the Web, and the Web increasingly impacts Publishing. Topic of particular interest to Publishing@W3C include typography and layout, accessibility, usability, portability, distribution, archiving, offline access, print on demand, and reliable cross referencing. And the diverse publishing community represented in the groups consist of the traditional "trade" publishers, ebook reading system manufacturers, but also publishers of audio book, scholarly journals or educational materials, library scientists or browser developers. The Publishing Working Group currently concentrates on Audiobooks which lack a comprehensive standard, thus incurring extra costs and time to publish in this booming market. Active development is ongoing on the future standard: Publication Manifest Audiobook profile for Web Publications Lightweight Packaging Format The BD Comics Manga Community Group, the Synchronized Multimedia for Publications Community Group, the Publishing Community Group and a future group on archival, are companions to the working group where specific work is developed and incubated. The Publishing Community Group is a recently launched incubation channel for Publishing@W3C. The goal of the group is to propose, document, and prototype features broadly related to: publications on the Web reading modes and systems and the user experience of publications The EPUB 3 Community Group has successfully completed the revision of EPUB 3.2. The Publishing Business Group fosters ongoing participation by members of the publishing industry and the overall ecosystem in the development of Web infrastructure to better support the needs of the industry. The Business Group serves as an additional conduit to the Publishing Working Group and several Community Groups for feedback between the publishing ecosystem and W3C. The Publishing BG has played a vital role in fostering and advancing the adoption and continued development of EPUB 3. In particular the BG provided critical support to the update of EPUBCheck to validate EPUB content to the new EPUB 3.2 specification. This resulted in the development, in conjunction with the EPUB3 Community Group, of a new generation of EPUBCheck, i.e., EPUBCheck 4.2 production-ready release. Media and Entertainment All Media specifications The Media and Entertainment vertical tracks media-related topics and features that create immersive experiences for end users. HTML5 brought standard audio and video elements to the Web. Standardization activities since then have aimed at turning the Web into a professional platform fully suitable for the delivery of media content and associated materials, enabling missing features to stream video content on the Web such as adaptive streaming and content protection. Together with Microsoft, Comcast, Netflix and Google, W3C received an Technology & Engineering Emmy Award in April 2019 for standardization of a full TV experience on the Web. Current goals are to: Reinforce core media technologies: Creation of the Media Working Group, to develop media-related specifications incubated in the WICG (e.g. Media Capabilities, Picture-in-picture, Media Session) and maintain maintain/evolve Media Source Extensions (MSE) and Encrypted Media Extensions (EME). Improve support for Media Timed Events: data cues incubation. Enhance color support (HDR, wide gamut), in scope of the CSS WG and in the Color on the Web CG. Reduce fragmentation: Continue annual releases of a common and testable baseline media devices, in scope of the Web Media APIs CG and in collaboration with the CTA WAVE Project. Maintain the Road-map of Media Technologies for the Web which highlights Web technologies that can be used to build media applications and services, as well as known gaps to enable additional use cases. Create the future: Discuss perspectives for Media and Entertainment for the Web. Bring the power of GPUs to the Web (graphics, machine learning, heavy processing), under incubation in the GPU for the Web CG. Transition to a Working Group is under discussion. Determine next steps after the successful W3C Workshop on Web Games of June 2019. View the report. Timed Text The Timed Text Working Group develops and maintains formats used for the representation of text synchronized with other timed media, like audio and video, and notably works on TTML, profiles of TTML, and WebVTT. Recent progress includes: A robust WebVTT implementation report poises the specification for publication as a proposed recommendation. Discussions around re-chartering, notably to add a TTML Profile for Audio Description deliverable to the scope of the group, and clarify that rendering of captions within XR content is also in scope. Immersive Web Hardware that enables Virtual Reality (VR) and Augmented Reality (AR) applications are now broadly available to consumers, offering an immersive computing platform with both new opportunities and challenges. The ability to interact directly with immersive hardware is critical to ensuring that the web is well equipped to operate as a first-class citizen in this environment. The Immersive Web Working Group has been stabilizing the WebXR Device API while the companion Immersive Web Community Group incubates the next series of features identified as key for the future of the Immersive Web. W3C plans a workshop focused on the needs and benefits at the intersection of VR & Accessibility (Inclusive XR), on 5-6 November 2019 in Seattle, WA, USA, to explore existing and future approaches on making Virtual and Augmented Reality experiences more inclusive. Web & Telecommunications The Web is the Open Platform for Mobile. Telecommunication service providers and network equipment providers have long been critical actors in the deployment of Web technologies. As the Web platform matures, it brings richer and richer capabilities to extend existing services to new users and devices, and propose new and innovative services. Real-Time Communications (WebRTC) All Real-Time Communications specifications WebRTC has reshaped the whole communication landscape by making any connected device a potential communication end-point, bringing audio and video communications anywhere, on any network, vastly expanding the ability of operators to reach their customers. WebRTC serves as the corner-stone of many online communication and collaboration services. The WebRTC Working Group aims to bringing WebRTC 1.0 (and companion specification Media Capture and Streams) to Recommendation by the end of 2019. Intense efforts are focused on testing (supported by a dedicated hackathon at IETF 104) and interoperability. The group is considering pushing features that have not gotten enough traction to separate modules or to a later minor revision of the spec. Beyond WebRTC 1.0, the WebRTC Working Group will focus its efforts on WebRTC NV which the group has started documenting by identifying use cases. Web & Networks Recently launched, in the wake of the May 2018 Web5G workshop, the Web & Networks Interest Group is chaired by representatives from AT&T, China Mobile and Intel, with a goal to explore solutions for web applications to achieve better performance and resource allocation, both on the device and network. The group's first efforts are around use cases, privacy & security requirements and liaisons. Automotive All Automotive specifications To create a rich application ecosystem for vehicles and other devices allowed to connect to the vehicle, the W3C Automotive Working Group is delivering a service specification to expose all common vehicle signals (engine temperature, fuel/charge level, range, tire pressure, speed, etc.) The Vehicle Information Service Specification (VISS), which is a Candidate Recommendation, is seeing more implementations across the industry. It provides the access method to a common data model for all the vehicle signals –presently encapsulating a thousand or so different data elements– and will be growing to accommodate the advances in automotive such as autonomous and driver assist technologies and electrification. The group is already working on a successor to VISS, leveraging the underlying data model and the VIWI submission from Volkswagen, for a more robust means of accessing vehicle signals information and the same paradigm for other automotive needs including location-based services, media, notifications and caching content. The Automotive and Web Platform Business Group acts as an incubator for prospective standards work. One of its task forces is using W3C VISS in performing data sampling and off-boarding the information to the cloud. Access to the wealth of information that W3C's auto signals standard exposes is of interest to regulators, urban planners, insurance companies, auto manufacturers, fleet managers and owners, service providers and others. In addition to components needed for data sampling and edge computing, capturing user and owner consent, information collection methods and handling of data are in scope. The upcoming W3C Workshop on Data Models for Transportation (September 2019) is expected to focus on the need of additional ontologies around transportation space. Web of Things All Web of Things specifications W3C's Web of Things work is designed to bridge disparate technology stacks to allow devices to work together and achieve scale, thus enabling the potential of the Internet of Things by eliminating fragmentation and fostering interoperability. Thing descriptions expressed in JSON-LD cover the behavior, interaction affordances, data schema, security configuration, and protocol bindings. The Web of Things complements existing IoT ecosystems to reduce the cost and risk for suppliers and consumers of applications that create value by combining multiple devices and information services. There are many sectors that will benefit, e.g. smart homes, smart cities, smart industry, smart agriculture, smart healthcare and many more. The Web of Things Working Group is finishing the initial Web of Things standards, with support from the Web of Things Interest Group: Web of Things Architecture Thing Descriptions Strengthening the Core of the Web HTML The HTML Working Group was chartered early June to assist the W3C community in raising issues and proposing solutions for the HTML and DOM specifications, and to produce W3C Recommendations from WHATWG Review Drafts. A few days before, W3C and the WHATWG signed a Memorandum of Understanding outlining the agreement to collaborate on the development of a single version of the HTML and DOM specifications. Issues and proposed solutions for HTML and DOM done via the newly rechartered HTML Working Group in the WHATWG repositories The HTML Working Group is targetting November 2019 to bring HTML and DOM to Candidate Recommendations. CSS All CSS specifications CSS is a critical part of the Open Web Platform. The CSS Working Group gathers requirements from two large groups of CSS users: the publishing industry and application developers. Within W3C, those groups are exemplified by the Publishing groups and the Web Platform Working Group. The former requires things like better pagination support and advanced font handling, the latter needs intelligent (and fast!) scrolling and animations. What we know as CSS is actually a collection of almost a hundred specifications, referred to as ‘modules’. The current state of CSS is defined by a snapshot, updated once a year. The group also publishes an index defining every term defined by CSS specifications. Fonts All Fonts specifications The Web Fonts Working Group develops specifications that allow the interoperable deployment of downloadable fonts on the Web, with a focus on Progressive Font Enrichment as well as maintenance of WOFF Recommendations. Recent and ongoing work includes: Early API experiments by Adobe and Monotype have demonstrated the feasibility of a font enrichment API, where a server delivers a font with minimal glyph repertoire and the client can query the full repertoire and request additional subsets on-the-fly. In other experiments, the Brotli compression used in WOFF 2 was extended to support shared dictionaries and patch update. Metrics to quantify improvement are a current hot discussion topic. The group will meet at ATypi 2019 in Japan, to gather requirements from the international typography community. The group will first produce a report summarizing the strengths and weaknesses of each prototype solution by Q2 2020. SVG All SVG specifications SVG is an important and widely-used part of the Open Web Platform. The SVG Working Group focuses on aligning the SVG 2.0 specification with browser implementations, having split the specification into a currently-implemented 2.0 and a forward-looking 2.1. Current activity is on stabilization, increased integration with the Open Web Platform, and test coverage analysis. The Working Group was rechartered in March 2019. A new work item concerns native (non-Web-browser) uses of SVG as a non-interactive, vector graphics format. Audio The Web Audio Working Group was extended to finish its work on the Web Audio API, expecting to publish it as a Recommendation by year end. The specification enables synthesizing audio in the browser. Audio operations are performed with audio nodes, which are linked together to form a modular audio routing graph. Multiple sources — with different types of channel layout — are supported. This modular design provides the flexibility to create complex audio functions with dynamic effects. The first version of Web Audio API is now feature complete and is implemented in all modern browsers. Work has started on the next version, and new features are being incubated in the Audio Community Group. Performance Web Performance All Web Performance specifications There are currently 18 specifications in development in the Web Performance Working Group aiming to provide methods to observe and improve aspects of application performance of user agent features and APIs. The W3C team is looking at related work incubated in the W3C GPU for the Web (WebGPU) Community Group which is poised to transition to a W3C Working Group. A preliminary draft charter is available. WebAssembly All WebAssembly specifications WebAssembly improves Web performance and power by being a virtual machine and execution environment enabling loaded pages to run native (compiled) code. It is deployed in Firefox, Edge, Safari and Chrome. The specification will soon reach Candidate Recommendation. WebAssembly enables near-native performance, optimized load time, and perhaps most importantly, a compilation target for existing code bases. While it has a small number of native types, much of the performance increase relative to Javascript derives from its use of consistent typing. WebAssembly leverages decades of optimization for compiled languages and the byte code is optimized for compactness and streaming (the web page starts executing while the rest of the code downloads). Network and API access all occurs through accompanying Javascript libraries -- the security model is identical to that of Javascript. Requirements gathering and language development occur in the Community Group while the Working Group manages test development, community review and progression of specifications on the Recommendation Track. Testing Browser testing plays a critical role in the growth of the Web by: Improving the reliability of Web technology definitions; Improving the quality of implementations of these technologies by helping vendors to detect bugs in their products; Improving the data available to Web developers on known bugs and deficiencies of Web technologies by publishing results of these tests. Browser Testing and Tools The Browser Testing and Tools Working Group is developing WebDriver version 2, having published last year the W3C Recommendation of WebDriver. WebDriver acts as a remote control interface that enables introspection and control of user agents, provides a platform- and language-neutral wire protocol as a way for out-of-process programs to remotely instruct the behavior of Web, and emulates the actions of a real person using the browser. WebPlatform Tests The WebPlatform Tests project now provides a mechanism which allows to fully automate tests that previously needed to be run manually: TestDriver. TestDriver enables sending trusted key and mouse events, sending complex series of trusted pointer and key interactions for things like in-content drag-and-drop or pinch zoom, and even file upload. Since 2014 W3C began work on this coordinated open-source effort to build a cross-browser test suite for the Web Platform, which WHATWG, and all major browsers adopted. Web of Data All Data specifications There have been several great success stories around the standardization of data on the web over the past year. Verifiable Claims seems to have significant uptake. It is also significant that the Distributed Identifier WG charter has received numerous favorable reviews, and was just recently launched. JSON-LD has been a major success with the large deployment on Web sites via schema.org. JSON-LD 1.1 completed technical work, about to transition to CR More than 25% of websites today include schema.org data in JSON-LD The Web of Things description is in CR since May, making use of JSON-LD Verifiable Credentials data model is in CR since July, also making use of JSON-LD Continued strong interest in decentralized identifiers Engagement from the TAG with reframing core documents, such as Ethical Web Principles, to include data on the web within their scope Data is increasingly important for all organizations, especially with the rise of IoT and Big Data. W3C has a mature and extensive suite of standards relating to data that were developed over two decades of experience, with plans for further work on making it easier for developers to work with graph data and knowledge graphs. Linked Data is about the use of URIs as names for things, the ability to dereference these URIs to get further information and to include links to other data. There are ever-increasing sources of open Linked Data on the Web, as well as data services that are restricted to the suppliers and consumers of those services. The digital transformation of industry is seeking to exploit advanced digital technologies. This will facilitate businesses to integrate horizontally along the supply and value chains, and vertically from the factory floor to the office floor. W3C is seeking to make it easier to support enterprise-wide data management and governance, reflecting the strategic importance of data to modern businesses. Traditional approaches to data have focused on tabular databases (SQL/RDBMS), Comma Separated Value (CSV) files, and data embedded in PDF documents and spreadsheets. We're now in midst of a major shift to graph data with nodes and labeled directed links between them. Graph data is: Faster than using SQL and associated JOIN operations More favorable to integrating data from heterogeneous sources Better suited to situations where the data model is evolving In the wake of the recent W3C Workshop on Graph Data we are in the process of launching a Graph Standardization Business Group to provide a business perspective with use cases and requirements, to coordinate technical standards work and liaisons with external organizations. Web for All Security, Privacy, Identity All Security specifications, all Privacy specifications Authentication on the Web As the WebAuthn Level 1 W3C Recommendation published last March is seeing wide implementation and adoption of strong cryptographic authentication, work is proceeding on Level 2. The open standard Web API gives native authentication technology built into native platforms, browsers, operating systems (including mobile) and hardware, offering protection against hacking, credential theft, phishing attacks, thus aiming to end the era of passwords as a security construct. You may read more in our March press release. Privacy An increasing number of W3C specifications are benefitting from Privacy and Security review; there are security and privacy aspects to every specification. Early review is essential. Working with the TAG, the Privacy Interest Group has updated the Self-Review Questionnaire: Security and Privacy. Other recent work of the group includes public blogging further to the exploration of anti-patterns in standards and permission prompts. Security The Web Application Security Working Group adopted Feature Policy, aiming to allow developers to selectively enable, disable, or modify the behavior of some of these browser features and APIs within their application; and Fetch Metadata, aiming to provide servers with enough information to make a priori decisions about whether or not to service a request based on the way it was made, and the context in which it will be used. The Web Payment Security Interest Group, launched last April, convenes members from W3C, EMVCo, and the FIDO Alliance to discuss cooperative work to enhance the security and interoperability of Web payments (read more about payments). Internationalization (i18n) All Internationalization specifications, educational articles related to Internationalization, spec developers checklist Only a quarter or so current Web users use English online and that proportion will continue to decrease as the Web reaches more and more communities of limited English proficiency. If the Web is to live up to the "World Wide" portion of its name, and for the Web to truly work for stakeholders all around the world engaging with content in various languages, it must support the needs of worldwide users as they engage with content in the various languages. The growth of epublishing also brings requirements for new features and improved typography on the Web. It is important to ensure the needs of local communities are captured. The W3C Internationalization Initiative was set up to increase in-house resources dedicated to accelerating progress in making the World Wide Web "worldwide" by gathering user requirements, supporting developers, and education & outreach. For an overview of current projects see the i18n radar. W3C's Internationalization efforts progressed on a number of fronts recently: Requirements: New African and European language groups will work on the gap analysis, errata and layout requirements. Gap analysis: Japanese, Devanagari, Bengali, Tamil, Lao, Khmer, Javanese, and Ethiopic updated in the gap-analysis documents. Layout requirements document: notable progress tracked in the Southeast Asian Task Force while work continues on Chinese layout requirements. Developer support: Spec reviews: the i18n WG continues active review of specifications of the WHATWG and other W3C Working Groups. Short review checklist: easy way to begin a self-review to help spec developers understand what aspects of their spec are likely to need attention for internationalization, and points them to more detailed checklists for the relevant topics. It also helps those reviewing specs for i18n issues. Strings on the Web: Language and Direction Metadata lays out issues and discusses potential solutions for passing information about language and direction with strings in JSON or other data formats. The document was rewritten for clarity, and expanded. The group is collaborating with the JSON-LD and Web Publishing groups to develop a plan for updating RDF, JSON-LD and related specifications to handle metadata for base direction of text (bidi). User-friendly test format: a new format was developed for Internationalization Test Suite tests, which displays helpful information about how the test works. This particularly useful because those tests are pointed to by educational materials and gap-analysis documents. Web Platform Tests: a large number of tests in the i18n test suite have been ported to the WPT repository, including: css-counter-styles, css-ruby, css-syntax, css-test, css-text-decor, css-writing-modes, and css-pseudo. Education & outreach: (for all educational materials, see the HTML & CSS Authoring Techniques) Web Accessibility All Accessibility specifications, WAI resources The Web Accessibility Initiative supports W3C's Web for All mission. Recent achievements include: Education and training: Inaccessibility of CAPTCHA updated to bring our analysis and recommendations up to date with CAPTCHA practice today, concluding two years of extensive work and invaluable input from the public (read more on the W3C Blog Learn why your web content and applications should be accessible. The Education and Outreach Working Group has completed revision and updating of the Business Case for Digital Accessibility. Accessibility guidelines: The Accessibility Guidelines Working Group has continued to update WCAG Techniques and Understanding WCAG 2.1; and published a Candidate Recommendation of Accessibility Conformance Testing Rules Format 1.0 to improve inter-rater reliability when evaluating conformance of web content to WCAG An updated charter is being developed to host work on "Silver", the next generation accessibility guidelines (WCAG 2.2) There are accessibility aspects to most specifications. Check your work with the FAST checklist. Outreach to the world W3C Developer Relations To foster the excellent feedback loop between Web Standards development and Web developers, and to grow participation from that diverse community, recent W3C Developer Relations activities include: @w3cdevs tracks the enormous amount of work happening across W3C W3C Track during the Web Conference 2019 in San Francisco Tech videos: W3C published the 2019 Web Games Workshop videos The 16 September 2019 Developer Meetup in Fukuoka, Japan, is open to all and will combine a set of technical demos prepared by W3C groups, and a series of talks on a selected set of W3C technologies and projects W3C is involved with Mozilla, Google, Samsung, Microsoft and Bocoup in the organization of ViewSource 2019 in Amsterdam (read more on the W3C Blog) W3C Training In partnership with EdX, W3C's MOOC training program, W3Cx offers a complete "Front-End Web Developer" (FEWD) professional certificate program that consists of a suite of five courses on the foundational languages that power the Web: HTML5, CSS and JavaScript. We count nearly 900K students from all over the world. Translations Many Web users rely on translations of documents developed at W3C whose official language is English. W3C is extremely grateful to the continuous efforts of its community in ensuring our various deliverables in general, and in our specifications in particular, are made available in other languages, for free, ensuring their exposure to a much more diverse set of readers. Last Spring we developed a more robust system, a new listing of translations of W3C specifications and updated the instructions on how to contribute to our translation efforts. W3C Liaisons Liaisons and coordination with numerous organizations and Standards Development Organizations (SDOs) is crucial for W3C to: make sure standards are interoperable coordinate our respective agenda in Internet governance: W3C participates in ICANN, GIPO, IGF, the I* organizations (ICANN, IETF, ISOC, IAB). ensure at the government liaison level that our standards work is officially recognized when important to our membership so that products based on them (often done by our members) are part of procurement orders. W3C has ARO/PAS status with ISO. W3C participates in the EU MSP and Rolling Plan on Standardization ensure the global set of Web and Internet standards form a compatible stack of technologies, at the technical and policy level (patent regime, fragmentation, use in policy making) promote Standards adoption equally by the industry, the public sector, and the public at large Coralie Mercier, Editor, W3C Marketing & Communications $Id: Overview.html,v 1.60 2019/10/15 12:05:52 coralie Exp $ Copyright © 2019 W3C ® (MIT, ERCIM, Keio, Beihang) Usage policies apply.
yzyouzhang / AIR ASVspoofOfficial implementation of the SPL paper "One-class Learning Towards Synthetic Voice Spoofing Detection"
PINTO0309 / Keras OneClassAnomalyDetection[5 FPS - 150 FPS] Learning Deep Features for One-Class Classification (AnomalyDetection). Corresponds RaspberryPi3. Convert to Tensorflow, ONNX, Caffe, PyTorch. Implementation by Python + OpenVINO/Tensorflow Lite.
ashishpatel26 / Titanic Machine Learning From DisasterStart here if... You're new to data science and machine learning, or looking for a simple intro to the Kaggle prediction competitions. Competition Description The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 1502 out of 2224 passengers and crew. This sensational tragedy shocked the international community and led to better safety regulations for ships. One of the reasons that the shipwreck led to such loss of life was that there were not enough lifeboats for the passengers and crew. Although there was some element of luck involved in surviving the sinking, some groups of people were more likely to survive than others, such as women, children, and the upper-class. In this challenge, we ask you to complete the analysis of what sorts of people were likely to survive. In particular, we ask you to apply the tools of machine learning to predict which passengers survived the tragedy. Practice Skills Binary classification Python and R basics
Aryia-Behroziuan / NeuronsAn ANN is a model based on a collection of connected units or nodes called "artificial neurons", which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit information, a "signal", from one artificial neuron to another. An artificial neuron that receives a signal can process it and then signal additional artificial neurons connected to it. In common ANN implementations, the signal at a connection between artificial neurons is a real number, and the output of each artificial neuron is computed by some non-linear function of the sum of its inputs. The connections between artificial neurons are called "edges". Artificial neurons and edges typically have a weight that adjusts as learning proceeds. The weight increases or decreases the strength of the signal at a connection. Artificial neurons may have a threshold such that the signal is only sent if the aggregate signal crosses that threshold. Typically, artificial neurons are aggregated into layers. Different layers may perform different kinds of transformations on their inputs. Signals travel from the first layer (the input layer) to the last layer (the output layer), possibly after traversing the layers multiple times. The original goal of the ANN approach was to solve problems in the same way that a human brain would. However, over time, attention moved to performing specific tasks, leading to deviations from biology. Artificial neural networks have been used on a variety of tasks, including computer vision, speech recognition, machine translation, social network filtering, playing board and video games and medical diagnosis. Deep learning consists of multiple hidden layers in an artificial neural network. This approach tries to model the way the human brain processes light and sound into vision and hearing. Some successful applications of deep learning are computer vision and speech recognition.[68] Decision trees Main article: Decision tree learning Decision tree learning uses a decision tree as a predictive model to go from observations about an item (represented in the branches) to conclusions about the item's target value (represented in the leaves). It is one of the predictive modeling approaches used in statistics, data mining, and machine learning. Tree models where the target variable can take a discrete set of values are called classification trees; in these tree structures, leaves represent class labels and branches represent conjunctions of features that lead to those class labels. Decision trees where the target variable can take continuous values (typically real numbers) are called regression trees. In decision analysis, a decision tree can be used to visually and explicitly represent decisions and decision making. In data mining, a decision tree describes data, but the resulting classification tree can be an input for decision making. Support vector machines Main article: Support vector machines Support vector machines (SVMs), also known as support vector networks, are a set of related supervised learning methods used for classification and regression. Given a set of training examples, each marked as belonging to one of two categories, an SVM training algorithm builds a model that predicts whether a new example falls into one category or the other.[69] An SVM training algorithm is a non-probabilistic, binary, linear classifier, although methods such as Platt scaling exist to use SVM in a probabilistic classification setting. In addition to performing linear classification, SVMs can efficiently perform a non-linear classification using what is called the kernel trick, implicitly mapping their inputs into high-dimensional feature spaces. Illustration of linear regression on a data set. Regression analysis Main article: Regression analysis Regression analysis encompasses a large variety of statistical methods to estimate the relationship between input variables and their associated features. Its most common form is linear regression, where a single line is drawn to best fit the given data according to a mathematical criterion such as ordinary least squares. The latter is often extended by regularization (mathematics) methods to mitigate overfitting and bias, as in ridge regression. When dealing with non-linear problems, go-to models include polynomial regression (for example, used for trendline fitting in Microsoft Excel[70]), logistic regression (often used in statistical classification) or even kernel regression, which introduces non-linearity by taking advantage of the kernel trick to implicitly map input variables to higher-dimensional space. Bayesian networks Main article: Bayesian network A simple Bayesian network. Rain influences whether the sprinkler is activated, and both rain and the sprinkler influence whether the grass is wet. A Bayesian network, belief network, or directed acyclic graphical model is a probabilistic graphical model that represents a set of random variables and their conditional independence with a directed acyclic graph (DAG). For example, a Bayesian network could represent the probabilistic relationships between diseases and symptoms. Given symptoms, the network can be used to compute the probabilities of the presence of various diseases. Efficient algorithms exist that perform inference and learning. Bayesian networks that model sequences of variables, like speech signals or protein sequences, are called dynamic Bayesian networks. Generalizations of Bayesian networks that can represent and solve decision problems under uncertainty are called influence diagrams. Genetic algorithms Main article: Genetic algorithm A genetic algorithm (GA) is a search algorithm and heuristic technique that mimics the process of natural selection, using methods such as mutation and crossover to generate new genotypes in the hope of finding good solutions to a given problem. In machine learning, genetic algorithms were used in the 1980s and 1990s.[71][72] Conversely, machine learning techniques have been used to improve the performance of genetic and evolutionary algorithms.[73] Training models Usually, machine learning models require a lot of data in order for them to perform well. Usually, when training a machine learning model, one needs to collect a large, representative sample of data from a training set. Data from the training set can be as varied as a corpus of text, a collection of images, and data collected from individual users of a service. Overfitting is something to watch out for when training a machine learning model. Federated learning Main article: Federated learning Federated learning is an adapted form of distributed artificial intelligence to training machine learning models that decentralizes the training process, allowing for users' privacy to be maintained by not needing to send their data to a centralized server. This also increases efficiency by decentralizing the training process to many devices. For example, Gboard uses federated machine learning to train search query prediction models on users' mobile phones without having to send individual searches back to Google.[74] Applications There are many applications for machine learning, including: Agriculture Anatomy Adaptive websites Affective computing Banking Bioinformatics Brain–machine interfaces Cheminformatics Citizen science Computer networks Computer vision Credit-card fraud detection Data quality DNA sequence classification Economics Financial market analysis[75] General game playing Handwriting recognition Information retrieval Insurance Internet fraud detection Linguistics Machine learning control Machine perception Machine translation Marketing Medical diagnosis Natural language processing Natural language understanding Online advertising Optimization Recommender systems Robot locomotion Search engines Sentiment analysis Sequence mining Software engineering Speech recognition Structural health monitoring Syntactic pattern recognition Telecommunication Theorem proving Time series forecasting User behavior analytics In 2006, the media-services provider Netflix held the first "Netflix Prize" competition to find a program to better predict user preferences and improve the accuracy of its existing Cinematch movie recommendation algorithm by at least 10%. A joint team made up of researchers from AT&T Labs-Research in collaboration with the teams Big Chaos and Pragmatic Theory built an ensemble model to win the Grand Prize in 2009 for $1 million.[76] Shortly after the prize was awarded, Netflix realized that viewers' ratings were not the best indicators of their viewing patterns ("everything is a recommendation") and they changed their recommendation engine accordingly.[77] In 2010 The Wall Street Journal wrote about the firm Rebellion Research and their use of machine learning to predict the financial crisis.[78] In 2012, co-founder of Sun Microsystems, Vinod Khosla, predicted that 80% of medical doctors' jobs would be lost in the next two decades to automated machine learning medical diagnostic software.[79] In 2014, it was reported that a machine learning algorithm had been applied in the field of art history to study fine art paintings and that it may have revealed previously unrecognized influences among artists.[80] In 2019 Springer Nature published the first research book created using machine learning.[81] Limitations Although machine learning has been transformative in some fields, machine-learning programs often fail to deliver expected results.[82][83][84] Reasons for this are numerous: lack of (suitable) data, lack of access to the data, data bias, privacy problems, badly chosen tasks and algorithms, wrong tools and people, lack of resources, and evaluation problems.[85] In 2018, a self-driving car from Uber failed to detect a pedestrian, who was killed after a collision.[86] Attempts to use machine learning in healthcare with the IBM Watson system failed to deliver even after years of time and billions of dollars invested.[87][88] Bias Main article: Algorithmic bias Machine learning approaches in particular can suffer from different data biases. A machine learning system trained on current customers only may not be able to predict the needs of new customer groups that are not represented in the training data. When trained on man-made data, machine learning is likely to pick up the same constitutional and unconscious biases already present in society.[89] Language models learned from data have been shown to contain human-like biases.[90][91] Machine learning systems used for criminal risk assessment have been found to be biased against black people.[92][93] In 2015, Google photos would often tag black people as gorillas,[94] and in 2018 this still was not well resolved, but Google reportedly was still using the workaround to remove all gorillas from the training data, and thus was not able to recognize real gorillas at all.[95] Similar issues with recognizing non-white people have been found in many other systems.[96] In 2016, Microsoft tested a chatbot that learned from Twitter, and it quickly picked up racist and sexist language.[97] Because of such challenges, the effective use of machine learning may take longer to be adopted in other domains.[98] Concern for fairness in machine learning, that is, reducing bias in machine learning and propelling its use for human good is increasingly expressed by artificial intelligence scientists, including Fei-Fei Li, who reminds engineers that "There’s nothing artificial about AI...It’s inspired by people, it’s created by people, and—most importantly—it impacts people. It is a powerful tool we are only just beginning to understand, and that is a profound responsibility.”[99] Model assessments Classification of machine learning models can be validated by accuracy estimation techniques like the holdout method, which splits the data in a training and test set (conventionally 2/3 training set and 1/3 test set designation) and evaluates the performance of the training model on the test set. In comparison, the K-fold-cross-validation method randomly partitions the data into K subsets and then K experiments are performed each respectively considering 1 subset for evaluation and the remaining K-1 subsets for training the model. In addition to the holdout and cross-validation methods, bootstrap, which samples n instances with replacement from the dataset, can be used to assess model accuracy.[100] In addition to overall accuracy, investigators frequently report sensitivity and specificity meaning True Positive Rate (TPR) and True Negative Rate (TNR) respectively. Similarly, investigators sometimes report the false positive rate (FPR) as well as the false negative rate (FNR). However, these rates are ratios that fail to reveal their numerators and denominators. The total operating characteristic (TOC) is an effective method to express a model's diagnostic ability. TOC shows the numerators and denominators of the previously mentioned rates, thus TOC provides more information than the commonly used receiver operating characteristic (ROC) and ROC's associated area under the curve (AUC).[101] Ethics Machine learning poses a host of ethical questions. Systems which are trained on datasets collected with biases may exhibit these biases upon use (algorithmic bias), thus digitizing cultural prejudices.[102] For example, using job hiring data from a firm with racist hiring policies may lead to a machine learning system duplicating the bias by scoring job applicants against similarity to previous successful applicants.[103][104] Responsible collection of data and documentation of algorithmic rules used by a system thus is a critical part of machine learning. Because human languages contain biases, machines trained on language corpora will necessarily also learn these biases.[105][106] Other forms of ethical challenges, not related to personal biases, are more seen in health care. There are concerns among health care professionals that these systems might not be designed in the public's interest but as income-generating machines. This is especially true in the United States where there is a long-standing ethical dilemma of improving health care, but also increasing profits. For example, the algorithms could be designed to provide patients with unnecessary tests or medication in which the algorithm's proprietary owners hold stakes. There is huge potential for machine learning in health care to provide professionals a great tool to diagnose, medicate, and even plan recovery paths for patients, but this will not happen until the personal biases mentioned previously, and these "greed" biases are addressed.[107] Hardware Since the 2010s, advances in both machine learning algorithms and computer hardware have led to more efficient methods for training deep neural networks (a particular narrow subdomain of machine learning) that contain many layers of non-linear hidden units.[108] By 2019, graphic processing units (GPUs), often with AI-specific enhancements, had displaced CPUs as the dominant method of training large-scale commercial cloud AI.[109] OpenAI estimated the hardware compute used in the largest deep learning projects from AlexNet (2012) to AlphaZero (2017), and found a 300,000-fold increase in the amount of compute required, with a doubling-time trendline of 3.4 months.[110][111] Software Software suites containing a variety of machine learning algorithms include the following: Free and open-source so
sanusanth / C Basic ProgramsWhat is C#? C# is pronounced "C-Sharp". It is an object-oriented programming language created by Microsoft that runs on the .NET Framework. C# has roots from the C family, and the language is close to other popular languages like C++ and Java. The first version was released in year 2002. The latest version, C# 8, was released in September 2019. C# is a modern object-oriented programming language developed in 2000 by Anders Hejlsberg, the principal designer and lead architect at Microsoft. It is pronounced as "C-Sharp," inspired by the musical notation “♯” which stands for a note with a slightly higher pitch. As it’s considered an incremental compilation of the C++ language, the name C “sharp” seemed most appropriate. The sharp symbol, however, has been replaced by the keyboard friendly “#” as a suffix to “C” for purposes of programming. Although the code is very similar to C++, C# is newer and has grown fast with extensive support from Microsoft. The fact that it’s so similar to Java syntactically helps explain why it has emerged as one of the most popular programming languages today. C# is pronounced "C-Sharp". It is an object-oriented programming language created by Microsoft that runs on the .NET Framework. C# has roots from the C family, and the language is close to other popular languages like C++ and Java. The first version was released in year 2002. The latest version, C# 8, was released in September 2019. C# is used for: Mobile applications Desktop applications Web applications Web services Web sites Games VR Database applications And much, much more! An Introduction to C# Programming C# is a general-purpose, object-oriented programming language that is structured and easy to learn. It runs on Microsoft’s .Net Framework and can be compiled on a variety of computer platforms. As the syntax is simple and easy to learn, developers familiar with C, C++, or Java have found a comfort zone within C#. C# is a boon for developers who want to build a wide range of applications on the .NET Framework—Windows applications, Web applications, and Web services—in addition to building mobile apps, Windows Store apps, and enterprise software. It is thus considered a powerful programming language and features in every developer’s cache of tools. Although first released in 2002, when it was introduced with .NET Framework 1.0, the C# language has evolved a great deal since then. The most recent version is C# 8.0, available in preview as part of Visual Studio. To get access to all of the new language features, you would need to install the latest preview version of .NET Core 3.0. C# is used for: Mobile applications Desktop applications Web applications Web services Web sites Games VR Database applications And much, much more! Why Use C#? It is one of the most popular programming language in the world It is easy to learn and simple to use It has a huge community support C# is an object oriented language which gives a clear structure to programs and allows code to be reused, lowering development costs. As C# is close to C, C++ and Java, it makes it easy for programmers to switch to C# or vice versa. The C# Environment You need the .NET Framework and an IDE (integrated development environment) to work with the C# language. The .NET Framework The .NET Framework platform of the Windows OS is required to write web and desktop-based applications using not only C# but also Visual Basic and Jscript, as the platform provides language interoperability. Besides, the .Net Framework allows C# to communicate with any of the other common languages, such as C++, Jscript, COBOL, and so on. IDEs Microsoft provides various IDEs for C# programming: Visual Studio 2010 (VS) Visual Studio Express Visual Web Developer Visual Studio Code (VSC) The C# source code files can be written using a basic text editor, like Notepad, and compiled using the command-line compiler of the .NET Framework. Alternative open-source versions of the .Net Framework can work on other operating systems as well. For instance, the Mono has a C# compiler and runs on several operating systems, including Linux, Mac, Android, BSD, iOS, Windows, Solaris, and UNIX. This brings enhanced development tools to the developer. As C# is part of the .Net Framework platform, it has access to its enormous library of codes and components, such as Common Language Runtime (CLR), the .Net Framework Class Library, Common Language Specification, Common Type System, Metadata and Assemblies, Windows Forms, ASP.Net and ASP.Net AJAX, Windows Workflow Foundation (WF), Windows Communication Foundation (WCF), and LINQ. C# and Java C# and Java are high-level programming languages that share several similarities (as well as many differences). They are both object-oriented languages much influenced by C++. But while C# is suitable for application development in the Microsoft ecosystem from the front, Java is considered best for client-side web applications. Also, while C# has many tools for programming, Java has a larger arsenal of tools to choose from in IDEs and Text Editors. C# is used for virtual reality projects like games, mobile, and web applications. It is built specifically for Microsoft platforms and several non-Microsoft-based operating systems, like the Mono Project that works with Linux and OS X. Java is used for creating messaging applications and developing web-based and enterprise-based applications in open-source ecosystems. Both C# and Java support arrays. However, each language uses them differently. In C#, arrays are a specialization of the system; in Java, they are a direct specialization of the object. The C# programming language executes on the CLR. The source code is interpreted into bytecode, which is further compiled by the CLR. Java runs on any platform with the assistance of JRE (Java Runtime Environment). The written source code is first compiled into bytecode and then converted into machine code to be executed on a JRE. C# and C++ Although C# and C++ are both C-based languages with similar code, there are some differences. For one, C# is considered a component-oriented programming language, while C++ is a partial object-oriented language. Also, while both languages are compiled languages, C# compiles to CLR and is interpreted by.NET, but C++ compiles to machine code. The size of binaries in C# is much larger than in C++. Other differences between the two include the following: C# gives compiler errors and warnings, but C++ doesn’t support warnings, which may cause damage to the OS. C# runs in a virtual machine for automatic memory management. C++ requires you to manage memory manually. C# can create Windows, .NET, web, desktop, and mobile applications, but not stand-alone apps. C++ can create server-side, stand-alone, and console applications as it can work directly with the hardware. C++ can be used on any platform, while C# is targeted toward Windows OS. Generally, C++ being faster than C#, the former is preferred for applications where performance is essential. Features of C# The C# programming language has many features that make it more useful and unique when compared to other languages, including: Object-oriented language Being object-oriented, C# allows the creation of modular applications and reusable codes, an advantage over C++. As an object-oriented language, C# makes development and maintenance easier when project size grows. It supports all three object-oriented features: data encapsulation, inheritance, interfaces, and polymorphism. Simplicity C# is a simple language with a structured approach to problem-solving. Unsafe operations, like direct memory manipulation, are not allowed. Speed The compilation and execution time in C# is very powerful and fast. A Modern programming language C# programming is used for building scalable and interoperable applications with support for modern features like automatic garbage collection, error handling, debugging, and robust security. It has built-in support for a web service to be invoked from any app running on any platform. Type-safe Arrays and objects are zero base indexed and bound checked. There is an automatic checking of the overflow of types. The C# type safety instances support robust programming. Interoperability Language interoperability of C# maximizes code reuse for the efficiency of the development process. C# programs can work upon almost anything as a program can call out any native API. Consistency Its unified type system enables developers to extend the type system simply and easily for consistent behavior. Updateable C# is automatically updateable. Its versioning support enables complex frameworks to be developed and evolved. Component oriented C# supports component-oriented programming through the concepts of properties, methods, events, and attributes for self-contained and self-describing components of functionality for robust and scalable applications. Structured Programming Language The structured design and modularization in C# break a problem into parts, using functions for easy implementation to solve significant problems. Rich Library C# has a standard library with many inbuilt functions for easy and fast development. Prerequisites for Learning C# Basic knowledge of C or C++ or any programming language or programming fundamentals. Additionally, the OOP concept makes for a short learning curve of C#. Advantages of C# There are many advantages to the C# language that makes it a useful programming language compared to other languages like Java, C, or C++. These include: Being an object-oriented language, C# allows you to create modular, maintainable applications and reusable codes Familiar syntax Easy to develop as it has a rich class of libraries for smooth implementation of functions Enhanced integration as an application written in .NET will integrate and interpret better when compared to other NET technologies As C# runs on CLR, it makes it easy to integrate with components written in other languages It’s safe, with no data loss as there is no type-conversion so that you can write secure codes The automatic garbage collection keeps the system clean and doesn’t hang it during execution As your machine has to install the .NET Framework to run C#, it supports cross-platform Strong memory backup prevents memory leakage Programming support of the Microsoft ecosystem makes development easy and seamless Low maintenance cost, as C# can develop iOS, Android, and Windows Phone native apps The syntax is similar to C, C++, and Java, which makes it easier to learn and work with C# Useful as it can develop iOS, Android, and Windows Phone native apps with the Xamarin Framework C# is the most powerful programming language for the .NET Framework Fast development as C# is open source steered by Microsoft with access to open source projects and tools on Github, and many active communities contributing to the improvement What Can C Sharp Do for You? C# can be used to develop a wide range of: Windows client applications Windows libraries and components Windows services Web applications Native iOS and Android mobile apps Azure cloud applications and services Gaming consoles and gaming systems Video and virtual reality games Interoperability software like SharePoint Enterprise software Backend services and database programs AI and ML applications Distributed applications Hardware-level programming Virus and malware software GUI-based applications IoT devices Blockchain and distributed ledger technology C# Programming for Beginners: Introduction, Features and Applications By Simplilearn Last updated on Jan 20, 2020674 C# Programming for Beginners As a programmer, you’re motivated to master the most popular languages that will give you an edge in your career. There’s a vast number of programming languages that you can learn, but how do you know which is the most useful? If you know C and C++, do you need to learn C# as well? How similar is C# to Java? Does it become more comfortable for you to learn C# if you already know Java? Every developer and wannabe programmer asks these types of questions. So let us explore C# programming: how it evolved as an extension of C and why you need to learn it as a part of the Master’s Program in integrated DevOps for server-side execution. Are you a web developer or someone interested to build a website? Enroll for the Javascript Certification Training. Check out the course preview now! What is C#? C# is a modern object-oriented programming language developed in 2000 by Anders Hejlsberg, the principal designer and lead architect at Microsoft. It is pronounced as "C-Sharp," inspired by the musical notation “♯” which stands for a note with a slightly higher pitch. As it’s considered an incremental compilation of the C++ language, the name C “sharp” seemed most appropriate. The sharp symbol, however, has been replaced by the keyboard friendly “#” as a suffix to “C” for purposes of programming. Although the code is very similar to C++, C# is newer and has grown fast with extensive support from Microsoft. The fact that it’s so similar to Java syntactically helps explain why it has emerged as one of the most popular programming languages today. An Introduction to C# Programming C# is a general-purpose, object-oriented programming language that is structured and easy to learn. It runs on Microsoft’s .Net Framework and can be compiled on a variety of computer platforms. As the syntax is simple and easy to learn, developers familiar with C, C++, or Java have found a comfort zone within C#. C# is a boon for developers who want to build a wide range of applications on the .NET Framework—Windows applications, Web applications, and Web services—in addition to building mobile apps, Windows Store apps, and enterprise software. It is thus considered a powerful programming language and features in every developer’s cache of tools. Although first released in 2002, when it was introduced with .NET Framework 1.0, the C# language has evolved a great deal since then. The most recent version is C# 8.0, available in preview as part of Visual Studio. To get access to all of the new language features, you would need to install the latest preview version of .NET Core 3.0. The C# Environment You need the .NET Framework and an IDE (integrated development environment) to work with the C# language. The .NET Framework The .NET Framework platform of the Windows OS is required to write web and desktop-based applications using not only C# but also Visual Basic and Jscript, as the platform provides language interoperability. Besides, the .Net Framework allows C# to communicate with any of the other common languages, such as C++, Jscript, COBOL, and so on. IDEs Microsoft provides various IDEs for C# programming: Visual Studio 2010 (VS) Visual Studio Express Visual Web Developer Visual Studio Code (VSC) The C# source code files can be written using a basic text editor, like Notepad, and compiled using the command-line compiler of the .NET Framework. Alternative open-source versions of the .Net Framework can work on other operating systems as well. For instance, the Mono has a C# compiler and runs on several operating systems, including Linux, Mac, Android, BSD, iOS, Windows, Solaris, and UNIX. This brings enhanced development tools to the developer. As C# is part of the .Net Framework platform, it has access to its enormous library of codes and components, such as Common Language Runtime (CLR), the .Net Framework Class Library, Common Language Specification, Common Type System, Metadata and Assemblies, Windows Forms, ASP.Net and ASP.Net AJAX, Windows Workflow Foundation (WF), Windows Communication Foundation (WCF), and LINQ. C# and Java C# and Java are high-level programming languages that share several similarities (as well as many differences). They are both object-oriented languages much influenced by C++. But while C# is suitable for application development in the Microsoft ecosystem from the front, Java is considered best for client-side web applications. Also, while C# has many tools for programming, Java has a larger arsenal of tools to choose from in IDEs and Text Editors. C# is used for virtual reality projects like games, mobile, and web applications. It is built specifically for Microsoft platforms and several non-Microsoft-based operating systems, like the Mono Project that works with Linux and OS X. Java is used for creating messaging applications and developing web-based and enterprise-based applications in open-source ecosystems. Both C# and Java support arrays. However, each language uses them differently. In C#, arrays are a specialization of the system; in Java, they are a direct specialization of the object. The C# programming language executes on the CLR. The source code is interpreted into bytecode, which is further compiled by the CLR. Java runs on any platform with the assistance of JRE (Java Runtime Environment). The written source code is first compiled into bytecode and then converted into machine code to be executed on a JRE. C# and C++ Although C# and C++ are both C-based languages with similar code, there are some differences. For one, C# is considered a component-oriented programming language, while C++ is a partial object-oriented language. Also, while both languages are compiled languages, C# compiles to CLR and is interpreted by.NET, but C++ compiles to machine code. The size of binaries in C# is much larger than in C++. Other differences between the two include the following: C# gives compiler errors and warnings, but C++ doesn’t support warnings, which may cause damage to the OS. C# runs in a virtual machine for automatic memory management. C++ requires you to manage memory manually. C# can create Windows, .NET, web, desktop, and mobile applications, but not stand-alone apps. C++ can create server-side, stand-alone, and console applications as it can work directly with the hardware. C++ can be used on any platform, while C# is targeted toward Windows OS. Generally, C++ being faster than C#, the former is preferred for applications where performance is essential. Features of C# The C# programming language has many features that make it more useful and unique when compared to other languages, including: Object-oriented language Being object-oriented, C# allows the creation of modular applications and reusable codes, an advantage over C++. As an object-oriented language, C# makes development and maintenance easier when project size grows. It supports all three object-oriented features: data encapsulation, inheritance, interfaces, and polymorphism. Simplicity C# is a simple language with a structured approach to problem-solving. Unsafe operations, like direct memory manipulation, are not allowed. Speed The compilation and execution time in C# is very powerful and fast. A Modern programming language C# programming is used for building scalable and interoperable applications with support for modern features like automatic garbage collection, error handling, debugging, and robust security. It has built-in support for a web service to be invoked from any app running on any platform. Type-safe Arrays and objects are zero base indexed and bound checked. There is an automatic checking of the overflow of types. The C# type safety instances support robust programming. Interoperability Language interoperability of C# maximizes code reuse for the efficiency of the development process. C# programs can work upon almost anything as a program can call out any native API. Consistency Its unified type system enables developers to extend the type system simply and easily for consistent behavior. Updateable C# is automatically updateable. Its versioning support enables complex frameworks to be developed and evolved. Component oriented C# supports component-oriented programming through the concepts of properties, methods, events, and attributes for self-contained and self-describing components of functionality for robust and scalable applications. Structured Programming Language The structured design and modularization in C# break a problem into parts, using functions for easy implementation to solve significant problems. Rich Library C# has a standard library with many inbuilt functions for easy and fast development. Full Stack Java Developer Course The Gateway to Master Web DevelopmentEXPLORE COURSEFull Stack Java Developer Course Prerequisites for Learning C# Basic knowledge of C or C++ or any programming language or programming fundamentals. Additionally, the OOP concept makes for a short learning curve of C#. Advantages of C# There are many advantages to the C# language that makes it a useful programming language compared to other languages like Java, C, or C++. These include: Being an object-oriented language, C# allows you to create modular, maintainable applications and reusable codes Familiar syntax Easy to develop as it has a rich class of libraries for smooth implementation of functions Enhanced integration as an application written in .NET will integrate and interpret better when compared to other NET technologies As C# runs on CLR, it makes it easy to integrate with components written in other languages It’s safe, with no data loss as there is no type-conversion so that you can write secure codes The automatic garbage collection keeps the system clean and doesn’t hang it during execution As your machine has to install the .NET Framework to run C#, it supports cross-platform Strong memory backup prevents memory leakage Programming support of the Microsoft ecosystem makes development easy and seamless Low maintenance cost, as C# can develop iOS, Android, and Windows Phone native apps The syntax is similar to C, C++, and Java, which makes it easier to learn and work with C# Useful as it can develop iOS, Android, and Windows Phone native apps with the Xamarin Framework C# is the most powerful programming language for the .NET Framework Fast development as C# is open source steered by Microsoft with access to open source projects and tools on Github, and many active communities contributing to the improvement What Can C Sharp Do for You? C# can be used to develop a wide range of: Windows client applications Windows libraries and components Windows services Web applications Native iOS and Android mobile apps Azure cloud applications and services Gaming consoles and gaming systems Video and virtual reality games Interoperability software like SharePoint Enterprise software Backend services and database programs AI and ML applications Distributed applications Hardware-level programming Virus and malware software GUI-based applications IoT devices Blockchain and distributed ledger technology Who Should Learn the C# Programming Language and Why? C# is one of the most popular programming languages as it can be used for a variety of applications: mobile apps, game development, and enterprise software. What’s more, the C# 8.0 version is packed with several new features and enhancements to the C# language that can change the way developers write their C# code. The most important new features available are ‘null reference types,’ enhanced ‘pattern matching,’ and ‘async streams’ that help you to write more reliable and readable code. As you’re exposed to the fundamental programming concepts of C# in this course, you can work on projects that open the doors for you as a Full Stack Java Developer. So, upskill and master the C# language for a faster career trajectory and salary scope.
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