A curated collection of 1000+ agent skills from official dev teams and the community, compatible with Claude Code, Codex, Gemini CLI, Cursor, and more.
Repository Index
47,133 repositories indexed
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This repository contains the Hugging Face Agents Course.
Translated🥇Juejin Translation Project (掘金翻译计划, Gold Miner), possibly the largest and best English-to-Chinese technical translation community in the world, the translation platform that best understands readers and translators:
This is the Rust course used by the Android team at Google. It provides you the material to quickly teach Rust.
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
- machine-learning
- deep-learning
- deep-reinforcement-learning
- machine-learning-from-scratch
Translated🎈 Updated daily! A list of popular BitTorrent Trackers! / Updated every day! A list of BT Trackers popular across the whole web!
- tracker
- trackers
- trackerslist
- bittorrent
😎 A curated list of awesome GitHub Profile which updates in real time
- awesome-list
- awesome
- github
- github-readme
Roadmap to becoming an Artificial Intelligence Expert in 2022
TranslatedWhat? You dare trust AI to have your back? I bet you don't, so come learn the coolest, safest, and fastest language of the AI era. This book offers comprehensive and in-depth explanations, vivid and fitting examples, and Dove-chocolate-smooth content. This may be the most painstakingly written Rust tutorial in Chinese available today / Book
- rust-lang
- rust
- book
- chinese
Python sample codes and textbook for robotics algorithms.
A list of AI autonomous agents
This repository started out as a learning in public project for myself and has now become a structured learning map for many in the community. We have 3 years under our belt covering all things DevOps, including Principles, Processes, Tooling and Use Cases surrounding this vast topic.
Translatedabout learning Spring Boot via examples. Spring Boot tutorials and tech stack example code, quick and easy tutorials to get started.
- spring-boot
- spring-data-jpa
- mybatis
- thymeleaf
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
A one stop repository for generative AI research updates, interview resources, notebooks and much more!
This repository is maintained by Omar Santos (@santosomar) and includes thousands of resources related to ethical hacking, bug bounties, digital forensics and incident response (DFIR), AI security, vulnerability research, exploit development, reverse engineering, and more. 🔥 Also check: https://hackertraining.org
- hacking
- penetration-testing
- hacking-series
- cybersecurity
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Machine Learning Systems: Foundations, Scaling, Agentic AI, and Physical AI (Vols I–IV) • Harvard CS249r | https://mlsysbook.ai
- artificial-intelligence
- cloud-ml
- computer-systems
- courseware
If you want to become good at AI engineering & system design, join this newsletter 👇
- computer-science
- interview-questions
- software-engineering
- system-design
A set of best practices for JavaScript projects
- best-practices
- maintainability
- guidelines
- javascript
A complete daily plan for studying to become a machine learning engineer.
- machine-learning
- deep-learning
- artificial-intelligence
- software-engineer
TranslatedI am Yiyang (木易杨, Muyiyang), author of the official account "高级前端进阶" (Advanced Frontend Progression). I tackle one frontend interview question from a big tech company every day. I wish everyone progress every day, and in a year you will see a different self.
Translated:star2: Wiki of OI / ICPC for everyone. (An online walkthrough for a certain large game, containing cool arithmetic magic)
- oi
- oi-handbook
- data-structures
- algorithms
What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?