Stars
Master programming by recreating your favorite technologies from scratch.
freeCodeCamp.org's open-source codebase and curriculum. Learn math, programming, and computer science for free.
😎 Awesome lists about all kinds of interesting topics
A complete computer science study plan to become a software engineer.
🙃 A delightful community-driven (with 2,400+ contributors) framework for managing your zsh configuration. Includes 300+ optional plugins (rails, git, macOS, hub, docker, homebrew, node, php, python…
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Share, discover, and collect prompts from the community. Free and open source — self-host for your organization with complete privacy.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
The fastest path to AI-powered full stack observability, even for lean teams.
A topic-centric list of HQ open datasets.
📚 List of awesome university courses for learning Computer Science!
🍺 The missing package manager for macOS (or Linux)
Collection of Summer 2026 tech internships!
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
A library for efficient similarity search and clustering of dense vectors.
We write your reusable computer vision tools. 💜
Fish-like autosuggestions for zsh
OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
⚡ A Fast, Extensible Progress Bar for Python and CLI
🇨🇭 A React renderer for Three.js
A playbook for systematically maximizing the performance of deep learning models.
Open-sourced codes for MiniGPT-4 and MiniGPT-v2 (https://minigpt-4.github.io, https://minigpt-v2.github.io/)
HomeKit support for the impatient.
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
Code samples for my book "Neural Networks and Deep Learning"