216 skills found · Page 3 of 8
alteryx / Predict Correct AnswerPredict whether a student will correctly answer a problem based on past performance using automated feature engineering
Ildaron / Consciousness Is MeasurableConsciousness treated as an engineering problem. Curated datasets and benchmarks for measuring awareness, self-models, and memory across humans, animals, and machines.
Voley / Algorithmic ProblemsAlgorithm and data structure problems for software engineering interviews
cline / Cline BenchReal-world coding benchmarks derived from actual Cline user sessions. Tasks are challenging, verified, and represent genuine engineering problems solved in production.
1lonely6legend / Interview面试自动驾驶规划岗位中遇到的一些实际/数学问题。Some engineering problems encountered during interviews with autonomous driving planning algorithm engineers
zoebear / RadiaRadia is a tool designed to create an interactive and immerse environment to visualize code, and to augment the task of reverse engineering binaries. The tool takes decompiled binaries extracted through IDA Pro, and visualizes the call graph in 3D space as a force directed graph. Radia tags functions that could be potential problems, as well as giving the user specific insight into individual nodes and their contents and relationships to other functions. In the end, the hope is to improve the available tools for auditing code to readily identify and remediate problems, and ultimately, to make code less vulnerable to exploitation by malware.
Mouneshgouda / Insurance ClaimPrediction of Auto Insurance Claim detection • Problem statement is related is to insurance domain • Performed a key role in Machine learning : Data gathering, cleaning ,Feature engineering ,Feature Selection ,Data visualization Model building ,Hyper parameter tunning • It’s a Classification problem evaluated model using confusion matrix and model
sjoshi804 / GoldmanSachs Coding ChallengeThe problems (and my solutions to them) for my hacker rank assessment for the Goldman Sachs Software Engineering Internship for 2019 Summer
FranklineMisango / Algorithmic Trading And HFT ResearchQuantitave research and Engineering on various promisory strategies, existing quant problems and opportunities using Mathematics and Statistics with end-end Data Science workflows
asanet / Chemeng SolvedClassic problems in chemical engineering solved with matlab
yuhao-yang-cy / Sci Simulationssimulations of various science and engineering problems
utilForever / CubbyCityAnalyze the causes of urban engineering problems such as gentrification
nima0011 / Nima0011# Contributing to this repository <!-- omit in toc --> ## Getting started <!-- omit in toc --> Before you begin: - This site is powered by Node.js. Check to see if you're on the [version of node we support](contributing/development.md). - Have you read the [code of conduct](CODE_OF_CONDUCT.md)? - Check out the [existing issues](https://github.com/github/docs/issues) & see if we [accept contributions](#types-of-contributions-memo) for your type of issue. ### Use the 'make a contribution' button  Navigating a new codebase can be challenging, so we're making that a little easier. As you're using docs.github.com, you may come across an article that you want to make an update to. You can click on the **make a contribution** button right on that article, which will take you to the file in this repo where you'll make your changes. Before you make your changes, check to see if an [issue exists](https://github.com/github/docs/issues/) already for the change you want to make. ### Don't see your issue? Open one If you spot something new, open an issue using a [template](https://github.com/github/docs/issues/new/choose). We'll use the issue to have a conversation about the problem you want to fix. ### Ready to make a change? Fork the repo Fork using GitHub Desktop: - [Getting started with GitHub Desktop](https://docs.github.com/en/desktop/installing-and-configuring-github-desktop/getting-started-with-github-desktop) will guide you through setting up Desktop. - Once Desktop is set up, you can use it to [fork the repo](https://docs.github.com/en/desktop/contributing-and-collaborating-using-github-desktop/cloning-and-forking-repositories-from-github-desktop)! Fork using the command line: - [Fork the repo](https://docs.github.com/en/github/getting-started-with-github/fork-a-repo#fork-an-example-repository) so that you can make your changes without affecting the original project until you're ready to merge them. Fork with [GitHub Codespaces](https://github.com/features/codespaces): - [Fork, edit, and preview](https://docs.github.com/en/free-pro-team@latest/github/developing-online-with-codespaces/creating-a-codespace) using [GitHub Codespaces](https://github.com/features/codespaces) without having to install and run the project locally. ### Make your update: Make your changes to the file(s) you'd like to update. Here are some tips and tricks for [using the docs codebase](#working-in-the-githubdocs-repository). - Are you making changes to the application code? You'll need **Node.js v14** to run the site locally. See [contributing/development.md](contributing/development.md). - Are you contributing to markdown? We use [GitHub Markdown](contributing/content-markup-reference.md). ### Open a pull request When you're done making changes and you'd like to propose them for review, use the [pull request template](#pull-request-template) to open your PR (pull request). ### Submit your PR & get it reviewed - Once you submit your PR, others from the Docs community will review it with you. The first thing you're going to want to do is a [self review](#self-review). - After that, we may have questions, check back on your PR to keep up with the conversation. - Did you have an issue, like a merge conflict? Check out our [git tutorial](https://lab.github.com/githubtraining/managing-merge-conflicts) on how to resolve merge conflicts and other issues. ### Your PR is merged! Congratulations! The whole GitHub community thanks you. :sparkles: Once your PR is merged, you will be proudly listed as a contributor in the [contributor chart](https://github.com/github/docs/graphs/contributors). ### Keep contributing as you use GitHub Docs Now that you're a part of the GitHub Docs community, you can keep participating in many ways. **Learn more about contributing:** - [Types of contributions :memo:](#types-of-contributions-memo) - [:mega: Discussions](#mega-discussions) - [:beetle: Issues](#beetle-issues) - [:hammer_and_wrench: Pull requests](#hammer_and_wrench-pull-requests) - [:question: Support](#question-support) - [:earth_asia: Translations](#earth_asia-translations) - [:balance_scale: Site Policy](#balance_scale-site-policy) - [Starting with an issue](#starting-with-an-issue) - [Labels](#labels) - [Opening a pull request](#opening-a-pull-request) - [Working in the github/docs repository](#working-in-the-githubdocs-repository) - [Reviewing](#reviewing) - [Self review](#self-review) - [Pull request template](#pull-request-template) - [Suggested changes](#suggested-changes) - [Windows](#windows) ## Types of contributions :memo: You can contribute to the GitHub Docs content and site in several ways. This repo is a place to discuss and collaborate on docs.github.com! Our small, but mighty :muscle: docs team is maintaining this repo, to preserve our bandwidth, off topic conversations will be closed. ### :mega: Discussions Discussions are where we have conversations. If you'd like help troubleshooting a docs PR you're working on, have a great new idea, or want to share something amazing you've learned in our docs, join us in [discussions](https://github.com/github/docs/discussions). ### :beetle: Issues [Issues](https://docs.github.com/en/github/managing-your-work-on-github/about-issues) are used to track tasks that contributors can help with. If an issue has a triage label, we haven't reviewed it yet and you shouldn't begin work on it. If you've found something in the content or the website that should be updated, search open issues to see if someone else has reported the same thing. If it's something new, open an issue using a [template](https://github.com/github/docs/issues/new/choose). We'll use the issue to have a conversation about the problem you want to fix. ### :hammer_and_wrench: Pull requests A [pull request](https://docs.github.com/en/github/collaborating-with-issues-and-pull-requests/about-pull-requests) is a way to suggest changes in our repository. When we merge those changes, they should be deployed to the live site within 24 hours. :earth_africa: To learn more about opening a pull request in this repo, see [Opening a pull request](#opening-a-pull-request) below. ### :question: Support We are a small team working hard to keep up with the documentation demands of a continuously changing product. Unfortunately, we just can't help with support questions in this repository. If you are experiencing a problem with GitHub, unrelated to our documentation, please [contact GitHub Support directly](https://support.github.com/contact). Any issues, discussions, or pull requests opened here requesting support will be given information about how to contact GitHub Support, then closed and locked. If you're having trouble with your GitHub account, contact [Support](https://support.github.com/contact). ### :earth_asia: Translations This website is internationalized and available in multiple languages. The source content in this repository is written in English. We integrate with an external localization platform called [Crowdin](https://crowdin.com) and work with professional translators to localize the English content. **We do not currently accept contributions for translated content**, but we hope to in the future. ### :balance_scale: Site Policy GitHub's site policies are published on docs.github.com, too! If you find a typo in the site policy section, you can open a pull request to fix it. For anything else, see [the CONTRIBUTING guide in the site-policy repo](https://github.com/github/site-policy/blob/main/CONTRIBUTING.md). ## Starting with an issue You can browse existing issues to find something that needs help! ### Labels Labels can help you find an issue you'd like to help with. - The [`help wanted` label](https://github.com/github/docs/issues?q=is%3Aopen+is%3Aissue+label%3A%22help+wanted%22) is for problems or updates that anyone in the community can start working on. - The [`good first issue` label](https://github.com/github/docs/issues?q=is%3Aopen+is%3Aissue+label%3A%22good+first+issue%22) is for problems or updates we think are ideal for beginners. - The [`content` label](https://github.com/github/docs/issues?q=is%3Aopen+is%3Aissue+label%3Acontent) is for problems or updates in the content on docs.github.com. These will usually require some knowledge of Markdown. - The [`engineering` label](https://github.com/github/docs/issues?q=is%3Aopen+is%3Aissue+label%3Aengineering) is for problems or updates in the docs.github.com website. These will usually require some knowledge of JavaScript/Node.js or YAML to fix. ## Opening a pull request You can use the GitHub user interface :pencil2: for some small changes, like fixing a typo or updating a readme. You can also fork the repo and then clone it locally, to view changes and run your tests on your machine. ## Working in the github/docs repository Here's some information that might be helpful while working on a Docs PR: - [Development](/contributing/development.md) - This short guide describes how to get this app running on your local machine. - [Content markup reference](/contributing/content-markup-reference.md) - All of our content is written in GitHub-flavored Markdown, with some additional enhancements. - [Content style guide for GitHub Docs](/contributing/content-style-guide.md) - This guide covers GitHub-specific information about how we style our content and images. It also links to the resources we use for general style guidelines. - [Reusables](/data/reusables/README.md) - We use reusables to help us keep content up to date. Instead of writing the same long string of information in several articles, we create a reusable, then call it from the individual articles. - [Variables](/data/variables/README.md) - We use variables the same way we use reusables. Variables are for short strings of reusable text. - [Liquid](/contributing/liquid-helpers.md) - We use liquid helpers to create different versions of our content. - [Scripts](/script/README.md) - The scripts directory is the home for all of the scripts you can run locally. - [Tests](/tests/README.md) - We use tests to ensure content will render correctly on the site. Tests run automatically in your PR, and sometimes it's also helpful to run them locally. ## Reviewing We (usually the docs team, but sometimes GitHub product managers, engineers, or supportocats too!) review every single PR. The purpose of reviews is to create the best content we can for people who use GitHub. :yellow_heart: Reviews are always respectful, acknowledging that everyone did the best possible job with the knowledge they had at the time. :yellow_heart: Reviews discuss content, not the person who created it. :yellow_heart: Reviews are constructive and start conversation around feedback. ### Self review You should always review your own PR first. For content changes, make sure that you: - [ ] Confirm that the changes address every part of the content design plan from your issue (if there are differences, explain them). - [ ] Review the content for technical accuracy. - [ ] Review the entire pull request using the [localization checklist](contributing/localization-checklist.md). - [ ] Copy-edit the changes for grammar, spelling, and adherence to the style guide. - [ ] Check new or updated Liquid statements to confirm that versioning is correct. - [ ] Check that all of your changes render correctly in staging. Remember, that lists and tables can be tricky. - [ ] If there are any failing checks in your PR, troubleshoot them until they're all passing. ### Pull request template When you open a pull request, you must fill out the "Ready for review" template before we can review your PR. This template helps reviewers understand your changes and the purpose of your pull request. ### Suggested changes We may ask for changes to be made before a PR can be merged, either using [suggested changes](https://docs.github.com/en/github/collaborating-with-issues-and-pull-requests/incorporating-feedback-in-your-pull-request) or pull request comments. You can apply suggested changes directly through the UI. You can make any other changes in your fork, then commit them to your branch. As you update your PR and apply changes, mark each conversation as [resolved](https://docs.github.com/en/github/collaborating-with-issues-and-pull-requests/commenting-on-a-pull-request#resolving-conversations). ## Windows This site can be developed on Windows, however a few potential gotchas need to be kept in mind: 1. Regular Expressions: Windows uses `\r\n` for line endings, while Unix based systems use `\n`. Therefore when working on Regular Expressions, use `\r?\n` instead of `\n` in order to support both environments. The Node.js [`os.EOL`](https://nodejs.org/api/os.html#os_os_eol) property can be used to get an OS-specific end-of-line marker. 1. Paths: Windows systems use `\` for the path separator, which would be returned by `path.join` and others. You could use `path.posix`, `path.posix.join` etc and the [slash](https://ghub.io/slash) module, if you need forward slashes - like for constructing URLs - or ensure your code works with either. 1. Bash: Not every Windows developer has a terminal that fully supports Bash, so it's generally preferred to write [scripts](/script) in JavaScript instead of Bash.
FeatEng / FeatEngThe benchmark for LLMs designed to tackle one of the most knowledge-intensive tasks in data science: writing feature engineering code, which requires domain knowledge in addition to a deep understanding of the underlying problem and data structure.
MAGESH-K21 / E Cafe Management System Web ApplicationSaiCafe is a Online canteen food ordering and management system based on a scenario at Sri Sairam Engineering College, Chennai. We have been observing that in many canteens/mess/cafeteria in all Institution such as educational, IT Sectors and Factories are experiencing huge crowds during peak hours. Due to this there was prolonged queue in the billing as well as delivery place, this ultimately leads to wastage of time and human errors in accounting... To overcome this problem, we came with a solution Online food ordering in the café using our web application. In our application any Registered Person can able to view and place their food orders prior to their break time with facilitation of online payments. The user can select a particular slot on which he/she willing to take delivery of the food.
reddyprasade / Machine Learning Interview PreparationPrepare to Technical Skills Here are the essential skills that a Machine Learning Engineer needs, as mentioned Read me files. Within each group are topics that you should be familiar with. Study Tip: Copy and paste this list into a document and save to your computer for easy referral. Computer Science Fundamentals and Programming Topics Data structures: Lists, stacks, queues, strings, hash maps, vectors, matrices, classes & objects, trees, graphs, etc. Algorithms: Recursion, searching, sorting, optimization, dynamic programming, etc. Computability and complexity: P vs. NP, NP-complete problems, big-O notation, approximate algorithms, etc. Computer architecture: Memory, cache, bandwidth, threads & processes, deadlocks, etc. Probability and Statistics Topics Basic probability: Conditional probability, Bayes rule, likelihood, independence, etc. Probabilistic models: Bayes Nets, Markov Decision Processes, Hidden Markov Models, etc. Statistical measures: Mean, median, mode, variance, population parameters vs. sample statistics etc. Proximity and error metrics: Cosine similarity, mean-squared error, Manhattan and Euclidean distance, log-loss, etc. Distributions and random sampling: Uniform, normal, binomial, Poisson, etc. Analysis methods: ANOVA, hypothesis testing, factor analysis, etc. Data Modeling and Evaluation Topics Data preprocessing: Munging/wrangling, transforming, aggregating, etc. Pattern recognition: Correlations, clusters, trends, outliers & anomalies, etc. Dimensionality reduction: Eigenvectors, Principal Component Analysis, etc. Prediction: Classification, regression, sequence prediction, etc.; suitable error/accuracy metrics. Evaluation: Training-testing split, sequential vs. randomized cross-validation, etc. Applying Machine Learning Algorithms and Libraries Topics Models: Parametric vs. nonparametric, decision tree, nearest neighbor, neural net, support vector machine, ensemble of multiple models, etc. Learning procedure: Linear regression, gradient descent, genetic algorithms, bagging, boosting, and other model-specific methods; regularization, hyperparameter tuning, etc. Tradeoffs and gotchas: Relative advantages and disadvantages, bias and variance, overfitting and underfitting, vanishing/exploding gradients, missing data, data leakage, etc. Software Engineering and System Design Topics Software interface: Library calls, REST APIs, data collection endpoints, database queries, etc. User interface: Capturing user inputs & application events, displaying results & visualization, etc. Scalability: Map-reduce, distributed processing, etc. Deployment: Cloud hosting, containers & instances, microservices, etc. Move on to the final lesson of this course to find lots of sample practice questions for each topic!
WeiZhang-2023 / ESPFEM2DThe Smoothed Particle Finite Element Method (SPFEM) has gained popularity as one of the effective numerical methods for modelling geotechnical problems involving large deformations. To advance the research and application of SPFEM in geotechnical engineering, we present ESPFEM2D, a two-dimensional SPFEM open-source solver developed using MATLAB.
BlockchainLabs / KryptonEthereum has brought us tools like Smart Contract, Dapp and DAO creation, deployment, and management. We can easily pay someone without ever hitting the send button, access decentralized applications that cannot be censored or shut down and we can be part of Decentralized Autonomous Organizations. Mistakes were made, bugs were found, and recently, millions were lost. Some are calling The DAO hack the most expensive bug bounty ever held, but whoever said this certainly didn’t have his Ether invested in The DAO, as the situation regarding the seizure of the stolen funds doesn’t seem to be improving. The DAO happened, it failed, all we can do now is move on and learn from our mistakes. The problem is that if we keep learning from $50m errors, we’ll be the wisest and poorest people on the planet. That’s why it’s good to have training wheels sometimes. Ethereum is the perfect playground for skilled developers, but with its 700% value increase since creation, it has made Solidity, one of the programming languages in Ethereum, a very expensive toy. That’s why Krypton has launched an open invitation to all developers to poke around the Krypton blockchain and see what it has to offer. Krypton (KR) is an Ethereum-based cryptocurrency that allows users all the same features and perks (Smart Contracts, Dapps, DAOs, DACs) but for a lower “price.” Ethereum transaction fees, which are known as “Gas” are spent according to computational costs, which means that the higher the price of Ether, the higher those costs will be. covertress, the Krypton founder, and project manager said: We’ve contacted several faculties at major universities and invited them to use the KR chain for this purpose. All of this means that developers have a testbed for smart contracts and Dapps, which are less expensive to deploy in the KR blockchain, before moving on to a more mainstream environment like Ethereum. Krypton can now be considered as a “gateway” into Ethereum. The team isn’t planning to stay humble forever but will, however, take their time before deploying anything and becoming a direct competitor to Ethereum, allowing them to tighten up security and functionality before moving on to providing smart contracts and Dapp solutions for companies. If you liked this article follow us on Twitter @themerklenews and make sure to subscribe to our newsletter to receive the latest bitcoin and altcoin price analysis and the latest cryptocurrency news. Krypton – Smart Contracts and DAPPs Development for Business Systems & IoT Ticker: KR Algorithm: Dagger-Hashimoto Block Reward: 0.25 KR Block Target: 15 Seconds Listen Port: 17171 RPC Port: 8888 Total KR: ~2.669 Million Real-Time Total KR Ethereum-Based: Utilizes Smart Contracts, DAOs, DACs and DAPPs Block Explorer: http://explorer.krypton.rocks After years in the tech sector, for engineering, entertainment, travel & finance companies, I’ve turned my focus to blockchain and building a startup, Krypton, to help companies realize their distributed applications. $KR is my vision for an ultra-fast blockchain that can realize all of the features of Ethereum with fewer initial coins, faster speed and lower inflation. Krypton can do the same things as Ethereum. However, with Ethereum’s codebase being updated to safely deploy DAOs, DACs, and DAPPs, there will be an explosion of practical-use cases, especially in the Internet of Things field. Companies will be actively seeking experienced developers. KR is an alternative platform on which to deploy these new technologies and Krypton developers are ready to build these systems. Join me in connecting Ðapps devs with real-life applications. Let’s code the future. — covertress, Founder & Project Manager Krypton is now hiring Smart Contracts and Ðapps developers with experience in Solidity, JS, and node.js. Please join Krypton’s Slack to apply: http://slack.krypton.rocks
rohanmistry231 / Prompt Engineering Interview PreparationA focused resource for mastering prompt engineering, featuring practice problems, examples, and interview-oriented techniques for optimizing AI model interactions. Covers crafting effective prompts for NLP models like GPT and BERT, with Python-based exercises.
thieu1995 / EnoppyENOPPY: A Python Library for Engineering Optimization Problems
