961 skills found · Page 19 of 33
Maras13 / Git PlaygroundA hands-on repository for learning GitHub basics! Dive into beginner-friendly exercises that guide you through creating repositories, making commits, handling branches, resolving merge conflicts, and more. Perfect for building confidence in version control and open-source collaboration.
lnemec / How To Document Data Science ProjectsThis project is part of a blog article published at Medium. We like to give you a step by step guide on how to document your Python Data Science Project effectively as part of your machine learning model development. The solution, we propose, ensures that your documentation is version controlled, shipped with the source code executing your machine learning experiment and made available to your users or co-workers using generally available tools including sphinx, GitHub, Microsoft Azure DevOps, and Azure storage or Azure web Services.
moonshinesnoxj12 / Classroom70xOptimize digital learning with the Classroom70x toolkit on GitHub. Advanced features for professional educational management and automation.
Deep-Learning-101 / Natural Language Processing Paperhttps://deep-learning-101.github.io/Computer-Vision-Paper/ Natural Language Processing (自然語言處理)
microsoft / Global Copilot SummitThe theme of the summit is Adopt, Extend, and Build Copilot, and is attended by professional developers interested in learning more about AI, GitHub Copilot, Azure AI Studio, or Power Apps and how they can leverage them with M365 Copilot.
venkat-0706 / BlogspotI created a repository for my Data Science blogs, where I share insights, tutorials, and projects on topics like machine learning, AI, and data analysis. Check it out on GitHub!
fsrt16 / Introduction To Genomic Data Sciences Breast Cancer Detection# Breast-cancer-risk-prediction > Necessity, who is the mother of invention. – Plato* ## Welcome to my GitHub repository on Using Predictive Analytics model to diagnose breast cancer. --- ### Objective: The repository is a learning exercise to: * Apply the fundamental concepts of machine learning from an available dataset * Evaluate and interpret my results and justify my interpretation based on observed data set * Create notebooks that serve as computational records and document my thought process. The analysis is divided into four sections, saved in juypter notebooks in this repository 1. Identifying the problem and Data Sources 2. Exploratory Data Analysis 3. Pre-Processing the Data 4. Build model to predict whether breast cell tissue is malignant or Benign ### [Notebook 1](https://github.com/ShiroJean/Breast-cancer-risk-prediction/blob/master/NB1_IdentifyProblem%2BDataClean.ipynb): Identifying the problem and Getting data. **Notebook goal:Identify the types of information contained in our data set** In this notebook I used Python modules to import external data sets for the purpose of getting to know/familiarize myself with the data to get a good grasp of the data and think about how to handle the data in different ways. ### [Notebook 2](https://github.com/ShiroJean/Breast-cancer-risk-prediction/blob/master/NB2_ExploratoryDataAnalysis.ipynb) Exploratory Data Analysis **Notebook goal: Explore the variables to assess how they relate to the response variable** In this notebook, I am getting familiar with the data using data exploration and visualization techniques using python libraries (Pandas, matplotlib, seaborn. Familiarity with the data is important which will provide useful knowledge for data pre-processing) ### [Notebook 3](https://github.com/ShiroJean/Breast-cancer-risk-prediction/blob/master/NB3_DataPreprocesing.ipynb) Pre-Processing the data **Notebook goal:Find the most predictive features of the data and filter it so it will enhance the predictive power of the analytics model.** In this notebook I use feature selection to reduce high-dimension data, feature extraction and transformation for dimensionality reduction. This is essential in preparing the data before predictive models are developed. ### [Notebook 4](https://github.com/ShiroJean/Breast-cancer-risk-prediction/blob/master/NB4_PredictiveModelUsingSVM.ipynb) Predictive model using Support Vector Machine (svm) **Notebook goal: Construct predictive models to predict the diagnosis of a breast tumor.** In this notebook, I construct a predictive model using SVM machine learning algorithm to predict the diagnosis of a breast tumor. The diagnosis of a breast tumor is a binary variable (benign or malignant). I also evaluate the model using confusion matrix the receiver operating curves (ROC), which are essential in assessing and interpreting the fitted model. ### [Notebook 5](https://github.com/ShiroJean/Breast-cancer-risk-prediction/blob/master/NB_5%20OptimizingSVMClassifier.ipynb): Optimizing the Support Vector Classifier **Notebook goal: Construct predictive models to predict the diagnosis of a breast tumor.** In this notebook, I aim to tune parameters of the SVM Classification model using scikit-learn.
Digital-Forensics-Discord-Server / GitHubLearningPlaygroundFork this repo! Do a Pull Request! As many times as you want! Learn the ins and outs of how to contribute to GitHub! Make your mistakes here before you make them elsewhere more public!
COMSM0045-Applied-Deep-Learning / COMSM0045 Applied Deep Learning.github.ioUnit website
LinkedInLearning / AI Pair Programming With Github Copilot X 2108008This repo is for the LInkedin Learning course: AI Pair Programming with GitHub Copilot
evilsocket / OctofairyA machine learning based GitHub bot for Issues.
JonathanCrabbe / Symbolic PursuitGithub for the NIPS 2020 paper "Learning outside the black-box: at the pursuit of interpretable models"
CompPhysics / MLErasmusThis site contains all document relevant for the Machine Learning courses of the Erasmus+ network. Jupyter-book link at https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/intro.html.
Andyameta / GIt FlowLearning github flow
edouardpineau / InfoCatVAEGithub page for the preprint paper "InfoCatVAE: Representation Learning with Categorical Variational Autoencoders"
Ali-Alameer / AI FairnessThis GitHub repository offers resources to create fair and unbiased AI systems, including libraries, tools and tutorials on identifying and mitigating bias in machine learning models and implementing fairness in AI.
nancyyanyu / Machine Learning Study NotesStudying notes of ISLR, ESL, and other Machine Learning books. Check a more user friendly version on my personal website https://nancyyanyu.github.io/.
IbrahimSobh / Kaggle Flower Classification TPUsTPUs are powerful hardware accelerators specialized in deep learning tasks, now available on Kaggle. https://ibrahimsobh.github.io/kaggle-Flower-Classification-TPUs/
Oliver191 / MSc Thesis Predictive Maintenance BatteriesThe GitHub repository accompanying the MSc Thesis at Esade written by Oliver Caspers regarding the topic “Predictive Maintenance for Lithium-Ion Batteries: Predicting the Remaining Useful Life (RUL) using Data-Driven Machine Learning based on Real-World Battery Datasets”.
Stability-AI / Stability AI ToolkitExternal project in GitHub for marketing purposes. This repo will be used for code samples that accompany blog posts on https://stability.ai/learning-hub
