High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
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Python framework for creating, editing, and running Noisy Intermediate-Scale Quantum (NISQ) circuits.
C++ implementation of the Python Numpy library
A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
📐 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.
The machine learning toolkit for time series analysis in Python
StellarGraph - Machine Learning on Graphs
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
A modular active learning framework for Python
Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).
A collection of GICP-based fast point cloud registration algorithms
Python interface for igraph
Metric learning algorithms in Python
🧠+🎧 Build your music algorithms and AI models with the next-gen DAW 🔥
A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.
🎯 A comprehensive gradient-free optimization framework written in Python
Parsers and algorithms for computational chemistry logfiles
A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.
Hyperparameter optimization and feature selection for scikit-learn using evolutionary algorithms. A modern alternative to GridSearchCV and RandomizedSearchCV.
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