🧑🏫 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, ... 🧠
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.
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
Minimal and clean examples of machine learning algorithms implementations
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
📐 Compute distance between sequences. 30+ algorithms, pure python implementation, common interface, optional external libs usage.
PennyLane is an open-source quantum software platform for quantum computing, quantum machine learning, and quantum chemistry. Create meaningful quantum algorithms, from inspiration to implementation.
wxPython's Project Phoenix. A new implementation of wxPython, better, stronger, faster than he was before.
A curated list of community detection research papers with implementations.
- graph-clustering
- network-clustering
- clustering
- dimensionality-reduction
Clean PyTorch implementations of imitation and reward learning algorithms
- reward-learning
- inverse-reinforcement-learning
- imitation-learning
- gymnasium
Fast, modular reference implementation and easy training of Semantic Segmentation algorithms in PyTorch.
A curated list of gradient boosting research papers with implementations.
- gradient-boosting
- gradient-boosting-classifier
- gradient-boosting-machine
- gradient-boosted-trees
Implementation of some deep learning algorithms.
A curated list of Monte Carlo tree search papers with implementations.
Awesome list of AI reverse engineering and rebuilds: what AI agents took apart and recreated, and which ones really used REA (Reverse Engineer Anything).
Python-based implementations of algorithms for learning on imbalanced data.
A pygame API-compatible reimplementation for running `pygame`-style code inside Jupyter notebooks (backed by ipycanvas)