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List of Computer Science courses with video lectures.
🧑🏫 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, ... 🧠
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
📚 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.
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.
FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.
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
Python Implementation of Reinforcement Learning: An Introduction
Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc.
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
强化学习中文教程（蘑菇书🍄），在线阅读地址：https://datawhalechina.github.io/easy-rl/
A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.
This is the homepage of a new book entitled "Mathematical Foundations of Reinforcement Learning."
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
An API standard for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)