Search Results for "vs code ai"
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Showing 17 open source projects for "vs code ai"
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Automate contact and company data extractionGenerate leads at scale without building or maintaining scrapers. Use 10,000+ ready-made tools that handle authentication, pagination, and anti-bot protection. Pull data from business directories, social profiles, and public sources, then export to your CRM or database via API. Schedule recurring extractions, enrich existing datasets, and integrate with your workflows.
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Roadmap To Learn Generative AI In 2025
Basic Machine Learning Natural Language Processing Roadmap
Roadmap To Learn Generative AI In 2025 is a curated learning path focused on contemporary generative AI — covering large language models (LLMs), diffusion-based image generation, prompt engineering, multi-modal AI, fine-tuning techniques, and the practical considerations for deploying generative models. It’s aimed at learners and developers who already have some programming or ML basics and wish to specialize in generative AI, offering a modern, structured plan that reflects the state of the... -
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JSCamp InfoJobs
Content and exercises fromJSCamp InfoJobs
...The repo also links to jscamp.dev, where the videos and course materials are hosted, and explains that access is free, with an optional paid certificate that includes extra support like CV review, exercise feedback, and exclusive workshops. Detailed installation requirements are listed (modern browser, VS Code, Live Preview extension, Node.js 20+, Git, Docker, etc. -
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Software Design in Haskell
Software Design in Haskell
This repository accompanies a comprehensive guide to building large, maintainable Haskell systems, focusing on architecture, modularity, and practical design techniques. It presents patterns for separating pure domain logic from side effects, organizing code into layers and components that can be tested in isolation. Readers encounter multiple styles—MTL/typeclass constraints, tagless-final encodings, free and freer monads, ReaderT-style application environments—and learn when to apply each.... -
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ktrain
ktrain is a Python library that makes deep learning AI more accessible
ktrain is a Python library that makes deep learning and AI more accessible and easier to apply. ktrain is a lightweight wrapper for the deep learning library TensorFlow Keras (and other libraries) to help build, train, and deploy neural networks and other machine learning models. Inspired by ML framework extensions like fastai and ludwig, ktrain is designed to make deep learning and AI more accessible and easier to apply for both newcomers and experienced practitioners. ... -
Desktop and Mobile Device Management SoftwareDesktop Central is a unified endpoint management (UEM) solution that helps in managing servers, laptops, desktops, smartphones, and tablets from a central location.
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eBook
LaTeX book with examples, open-source eBook
LaTeX can be a challenging system to learn, but with this book of different examples, it becomes interesting and easier than ever. This comprehensive guide covers a lot of essentials and is written in a clear and concise style, showing the result vs code. Plus, it's #opensource and freely available, creating a collaborative learning environment. In this book the I try to reveal how you can find necessary pieces of TeX code looking only at already done work. If you want to create high-quality documents with LaTeX, check out the LaTaX book on GitHub, and feel free to ask any questions you have. -
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Quiz/Survey/Test - QST
A Free, complete, enterprise grade, open source exam management system
QST, the worlds unparalleled open source online/lan assessment software. From a quick quiz on your phone to very large scale, high stakes, proctored desktop testing, we make it easy/secure/economical. Our intuitive design contains features (Immediate detailed results, Create/Export/Import/Convert Questions, WYSIWYG/Math-Chemistry/Basic Editors, Question/Item Bank, Multiple Question Types, Multiple Delivery Styles, Multiple Delivery/Results Options, Adaptive/Branching Questions, Randomly... -
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The Art of Programming
A collection of practical tips can be found at the bottom of this page
The Art of Programming (Second Edition) is a curated collection of programming problems and solutions originally derived from the Microsoft 100 Interview Questions blog series, later refined into a long-running tutorial and ultimately a published book. Created by July, the series began in 2010 and has since evolved into an in-depth exploration of algorithmic thinking, data structures, and coding interview preparation. The repository brings together 42 classic programming problems from the... -
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Hello AI World
Guide to deploying deep-learning inference networks
Hello AI World is a great way to start using Jetson and experiencing the power of AI. In just a couple of hours, you can have a set of deep learning inference demos up and running for realtime image classification and object detection on your Jetson Developer Kit with JetPack SDK and NVIDIA TensorRT. The tutorial focuses on networks related to computer vision, and includes the use of live cameras. -
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DeepMind Educational Resources
DeepMind's repo of educational notebooks for learning AI and research
Educational is an open collection of interactive tutorials created by Google DeepMind to make the fundamentals of machine learning and artificial intelligence accessible to learners of all backgrounds. The repository provides hands-on, beginner-friendly resources that introduce essential AI concepts through Google Colab notebooks, combining intuitive explanations with executable code. The tutorials cover a broad range of topics—from foundational Python programming and data handling to supervised, unsupervised, and reinforcement learning, as well as graph neural networks and scientific reasoning. Specialized notebooks also explore creative AI applications, language modeling, generative models, and protein folding. ... -
Free and Open Source HR SoftwareGive your HR team the tools they need to streamline administrative tasks, support employees, and make informed decisions with the OrangeHRM free and open source HR software.
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Brain Tokyo Workshop
Experiments and code from Google Brain’s Tokyo research workshop
...The repository includes implementations, experimental data, and supporting research papers that accompany published studies. Notable works such as Weight Agnostic Neural Networks and Neuroevolution of Self-Interpretable Agents highlight the team’s exploration of how AI can learn more efficiently and transparently. Overall, this repository serves as an open research hub for sharing ideas and advancing the understanding of intelligent systems. -
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LTEX Extension for VS Code
LTeX: Grammar/spell checker for VS Code using LanguageTool
LTEX provides offline grammar checking of various markup languages using LanguageTool (LT). LTEX can be used standalone as a command-line tool, as a language server using the Language Server Protocol (LSP), or directly in various editors using extensions. LTEX currently supports BibTEX, ConTEXt, LATEX, Markdown, Org, reStructuredText, R Sweave, and XHTML documents. A classic use case of LTEX is checking scientific LATEX papers. -
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Machine Learning PyTorch Scikit-Learn
Code Repository for Machine Learning with PyTorch and Scikit-Learn
Initially, this project started as the 4th edition of Python Machine Learning. However, after putting so much passion and hard work into the changes and new topics, we thought it deserved a new title. So, what’s new? There are many contents and additions, including the switch from TensorFlow to PyTorch, new chapters on graph neural networks and transformers, a new section on gradient boosting, and many more that I will detail in a separate blog post. For those who are interested in knowing... -
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wav2letter++
Facebook AI research's automatic speech recognition toolkit
First, install Flashlight (using the 0.3 branch is required) with the ASR application. This repository includes recipes to reproduce the following research papers as well as pre-trained models. All results reproduction must use Flashlight <= 0.3.2 for exact reproducibility. At least one of LZMA, BZip2, or Z is required for LM compression with KenLM. It is highly recommended to build KenLM with position-independent code (-fPIC) enabled, to enable python compatibility. After installing, run... -
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Spinning Up in Deep RL
Educational resource to help anyone learn deep reinforcement learning
Welcome to Spinning Up in Deep RL! This is an educational resource produced by OpenAI that makes it easier to learn about deep reinforcement learning (deep RL). For the unfamiliar, reinforcement learning (RL) is a machine learning approach for teaching agents how to solve tasks by trial and error. Deep RL refers to the combination of RL with deep learning. At OpenAI, we believe that deep learning generally, and deep reinforcement learning specifically, will play central roles in the... -
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Deep Learning for Medical Applications
Deep Learning Papers on Medical Image Analysis
Deep-Learning-for-Medical-Applications is a repository that compiles deep learning methods, code implementations, and examples applied to medical imaging and healthcare data. The project addresses domain-specific challenges like segmentation, classification, detection, and multimodal data (e.g. MRI, CT, X-ray) using state-of-the-art architectures (e.g. U-Net, ResNet, GAN variants) tailored to medical constraints (small datasets, annotation costs, class imbalance). It includes Jupyter... -
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Open source clone of the board strategy game blokus, mainly the duo (1vs1) mode. Each player has 21 pieces to put on the board while preventing the opponent from doing the same. Also features solo or 4 players games and an expandable challenge mode.
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SAgent86 is the Java code for a participant agent in the Agent Reputation and Trust (ART) Testbed 0.3.4.
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