216 skills found · Page 4 of 8
civilcfd / Civil CFDFree-surface 3D CFD Solver for Civil Engineering Problems
Aaronontheweb / AkkaStreamsCookbookSome Akka.NET streams examples for solving common backpressure / engineering problems.
studium-ignotum / HoangsaHOANGSA is a context engineering system for Claude Code. It solves a fundamental problem: Claude's output quality degrades as the context window fills up.
kaustubh-karkare / Project OmegaA collection of non-trivial coding problems to improve software engineering skills.
kalpak92 / DataStructures AlgorithmsDataStructure and Algorithm problems for software engineering interviews.
profhsgill / PychemenggPyChemEngg is a python-based framework to promote problem solving and critical thinking in chemical engineering.
CallumJHays / MathpadType-hinted, simplified interface to `sympy` for solving engineering, science and maths problems.
tengjuilin / Cheme Sci ComputingUW CHEME 375 and applications in CHEME 310, 326. Chemical engineering scientific computing and numerical methods. Topics include curve fitting, balancing chemical equations, solving VLE problems, plotting VLE x/y and Txy diagrams, determining Antoine's coefficients, chemical kinetics, and time-dependent and -independent heat transfer.
4l3j4ndr0 / Strands Agents EcosystemA comprehensive multi-agent coordination system built with the Strands framework, demonstrating advanced "Agents as Tools" patterns for solving complex cloud engineering problems.
SajadAHMAD1 / CPSOCGSA For Engineering Design OptimizationConstriction Coefficient Based PSO and Chaotic GSA for Engineering Design Problems
tengjuilin / Intro Sci ComputingUW AMATH 301. Scientific computing and numerical methods for physical, biological, and engineering problems. Topics include root-finding, optimization, curve fitting, solving linear systems, singular value decomposition (SVD, PCA), numerical differentiation and integration, solving first-order and higher order ODEs, stability and stiffness of ODEs, phase portraits, chaotic systems, and Fourier transform.
diloabininyeri / Php Design PatternsPHP design patterns and PHPUnit test, In software engineering, a design pattern is a general repeatable solution to a commonly occurring problem in software design. A design pattern isn't a finished design that can be transformed directly into code. It is a description or template for how to solve a problem that can be used in many different situations.
newking9088 / MITx 6.86x Machine Learning With Python From Linear Models To Deep Learning Fall 2020Welcome to 6.86x Machine Learning with Python–From Linear Models to Deep Learning. Machine learning methods are commonly used across engineering and sciences, from computer systems to physics. Moreover, commercial sites such as search engines, recommender systems (e.g., Netflix, Amazon), advertisers, and financial institutions employ machine learning algorithms for content recommendation, predicting customer behavior, compliance, or risk. As a discipline, machine learning tries to design and understand computer programs that learn from experience for the purpose of prediction or control. In this course, you will learn about principles and algorithms for turning training data into effective automated predictions. We will cover: Representation, over-fitting, regularization, generalization, VC dimension; Clustering, classification, recommender problems, probabilistic modeling, reinforcement learning; On-line algorithms, support vector machines, and neural networks/deep learning. You will be able to: Understand principles behind machine learning problems such as classification, regression, clustering, and reinforcement learning Implement and analyze models such as linear models, kernel machines, neural networks, and graphical models Choose suitable models for different applications Implement and organize machine learning projects, from training, validation, parameter tuning, to feature engineering You will implement and experiment with the algorithms in several Python projects designed for different practical applications. You will expand your statistical knowledge to not only include a list of methods, but also the mathematical principles that link these methods together, equipping you with the tools you need to develop new ones.
EMETEM-GLOBAL-ENTERPRISE / Prototype# 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 strategy 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.
anoop-gupt / Frontend Engineering PlaybookA Playbook on Frontend engineering describing the best strategies and solutions for various day to day implementations and common problems.
YangYuSCU / DE PINNwith comprehensive numerical study on solving neutron diffusion eigenvalue problems) We present a data-enabled physics-informed neural network (DEPINN) with comprehensive numerical study for solving industrial scale neutron diffusion eigenvalue problems (NDEPs). In order to achieve an engineering acceptable accuracy for complex engineering problems, a very small amount of prior data from physical experiments are suggested to be used, to improve the accuracy and efficiency of training. We design an adaptive optimization procedure with Adam and LBFGS to accelerate the convergence in the training stage. We discuss the effect of different physical parameters, sampling techniques, loss function allocation and the generalization performance of the proposed DEPINN model for solving complex problem. The feasibility of proposed DEPINN model is tested on three typical benchmark problems, from simple geometry to complex geometry, and from mono-energetic equation to two-group equations. Numerous numerical results show that DEPINN can efficiently solve NDEPs with an appropriate optimization procedure. The proposed DEPINN can be generalized for other input parameter settings once its structure been trained. This work confirms the possibility of DEPINN for practical engineering applications in nuclear reactor physics.
UofR-ESI-Lab / Optimization TutorialThis workshop introduces basic concepts, models and algorithms in linear programming, convex optimization and stochastic optimization. A MATLAB-based modeling system for convex optimization, CVX, is covered. Case studies are presented including an production plan problem, smart electric vehicle charging, a newsvendor problem, and a regression model. The codes are provided for practice. The workshop is organized by IEEE South Sask section & PES/IAS Joint Chapter in collaboration with Engineering Graduate Student Association (EGSA) and the Faculty of Engineering and Applied Science at the University of Regina.
aliasgharheidaricom / RUN Beyond The Metaphor An Efficient Optimization Algorithm Based On Runge Kutta MethodThe optimization field suffers from the metaphor-based “pseudo-novel” or “fancy” optimizers. Most of these cliché methods mimic animals' searching trends and possess a small contribution to the optimization process itself. Most of these cliché methods suffer from the locally efficient performance, biased verification methods on easy problems, and high similarity between their components' interactions. This study attempts to go beyond the traps of metaphors and introduce a novel metaphor-free population-based optimization based on the mathematical foundations and ideas of the Runge Kutta (RK) method widely well-known in mathematics. The proposed RUNge Kutta optimizer (RUN) was developed to deal with various types of optimization problems in the future. The RUN utilizes the logic of slope variations computed by the RK method as a promising and logical searching mechanism for global optimization. This search mechanism benefits from two active exploration and exploitation phases for exploring the promising regions in the feature space and constructive movement toward the global best solution. Furthermore, an enhanced solution quality (ESQ) mechanism is employed to avoid the local optimal solutions and increase convergence speed. The RUN algorithm's efficiency was evaluated by comparing with other metaheuristic algorithms in 50 mathematical test functions and four real-world engineering problems. The RUN provided very promising and competitive results, showing superior exploration and exploitation tendencies, fast convergence rate, and local optima avoidance. In optimizing the constrained engineering problems, the metaphor-free RUN demonstrated its suitable performance as well. The authors invite the community for extensive evaluations of this deep-rooted optimizer as a promising tool for real-world optimization. The source codes, supplementary materials, and guidance for the developed method will be publicly available at different hubs at http://aliasgharheidari.com/RUN.html.
ohcnetwork / Admission TaskGlobal Digital Corps - Software Engineering Test Problem | Priority list
StevenShaw98 / Artificial Lemming AlgorithmArtificial lemming algorithm: A novel bionic meta-heuristic technique for solving real-world engineering optimization problems
