reinforcement-learning

List of Computer Science courses with video lectures.

Local UI to run and train LLMs and diffusion models, including Qwen3.8, Kimi K3, MiniMax-H3, Gemma 4, DeepSeek-V4, FLUX and more.

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

Learn it. Build it. Ship it for others.

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

《深入理解 AI Agent：设计原理与工程实践》（李博杰 著）开源主仓库：全书正文、编译版 PDF 与按章配套代码

SGLang is a high-performance serving framework for large language models and multimodal models.

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.

Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.

The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.

The absolute trainer to light up AI agents.

Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

《李宏毅深度学习教程》（李宏毅老师推荐👍，苹果书🍎），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases

Machine learning, in numpy

A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.

Python Implementation of Reinforcement Learning: An Introduction

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!