ml5.js - Friendly machine learning for the web.
imgaug - Image augmentation for machine learning experiments.
PlaidML - Framework for making deep learning work everywhere.
Leaf - Open Machine Intelligence Framework for Hackers. (GPU/CPU).
Apache MXNet - Deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity.
Sonnet - Library built on top of TensorFlow for building complex neural networks.
tvm - Open deep learning compiler stack for cpu, gpu and specialized accelerators.
dgl - Python package built to ease deep learning on graph, on top of existing DL frameworks.
PySyft - Library for encrypted, privacy preserving deep learning.
numpy-ml - Machine learning, in numpy.
cuML - Suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects.
ONNX Runtime - Cross-platform, high performance scoring engine for ML models.
MLflow - Machine Learning Lifecycle Platform.
auto-sklearn - Automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator.
TensorNetwork - Library for easy and efficient manipulation of tensor networks.
lambda-ml - Small machine learning library aimed at providing simple, concise implementations of machine learning techniques and utilities.
MLBox - Powerful Automated Machine Learning python library.
Mlxtend (machine learning extensions) - Python library of useful tools for the day-to-day data science tasks.
CrypTen - Framework for Privacy Preserving Machine Learning built on PyTorch.
Faiss - Library for efficient similarity search and clustering of dense vectors.
pyHSICLasso - Versatile Nonlinear Feature Selection Algorithm for High-dimensional Data.
AutoGluon - AutoML Toolkit for Deep Learning.
DeepLearning.scala - Simple library for creating complex neural networks from object-oriented and functional programming constructs.
Optuna - Hyperparameter optimization framework.
Vowpal Wabbit - Machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
Brancher - User-centered Python package for differentiable probabilistic inference.
Karate Club - General purpose community detection and network embedding library for research built on NetworkX.
FlexFlow - Distributed deep learning framework that supports flexible parallelization strategies.
DeltaPy - Tabular Data Augmentation & Feature Engineering.
TensorStore - Library for reading and writing large multi-dimensional arrays.
FATE - Industrial Level Federated Learning Framework.
Deepkit - Collaborative and real-time machine learning training suite: Experiment execution, tracking, and debugging.
Sls - Stochastic Line Search.
PyCaret - Open source low-code machine learning library in Python that aims to reduce the hypothesis to insights cycle time in a ML experiment.
Flax - Neural network library for JAX designed for flexibility.
scikit-multilearn - Python module capable of performing multi-label learning tasks.
imbalanced-learn - Python package offering a number of re-sampling techniques commonly used in datasets showing strong between-class imbalance.
DeepSpeed - Deep learning optimization library that makes distributed training easy, efficient, and effective.
HoMM - Library for Homoiconic Meta-mapping.
Hummingbird - Library for compiling trained traditional ML models into tensor computations.
Ax - Accessible, general-purpose platform for understanding, managing, deploying, and automating adaptive experiments.
Neuropod - Uniform interface to run deep learning models from multiple frameworks.
aerosolve - Machine learning package built for humans in Scala.
Kur - Descriptive Deep Learning.
NNI (Neural Network Intelligence) - Lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture Search, Hyperparameter Tuning and Model Compression.
LMfit-py - Non-Linear Least Squares Minimization, with flexible Parameter settings, based on scipy.optimize.leastsq, and with many additional classes and methods for curve fitting.
tslearn - Machine learning toolkit for time series analysis in Python.