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🧑🏫 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.
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.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.
Machine learning, in numpy
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility
Deep Reinforcement Learning for Keras.
Accelerated deep learning R&D
OpenAI Gym environments for an open-source quadruped robot (SpotMicro)
Modular Reinforcement Learning (RL) library (implemented in PyTorch, JAX, and NVIDIA Warp) with support for Gymnasium/Gym, NVIDIA Isaac Lab, MuJoCo Playground and other environments
A curated list of Monte Carlo tree search papers with implementations.
Maze Applied Reinforcement Learning Framework
Free Course : Data, Machine Learning, Deep Learning and AI Engineering, the long way round: the math, the code, the systems and the security. 173 lessons, 166 runnable labs, no shortcuts. Free under CC BY-NC 4.0.