Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

AutoML library for deep learning

Automated Machine Learning with scikit-learn

An open source python library for automated feature engineering

Fast and Accurate ML in 3 Lines of Code

Differentiable architecture search for convolutional and recurrent networks

An Automatic Model Compression (AutoMC) framework for developing smaller and faster AI applications.

Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™

ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

A Hyperparameter Tuning Library for Keras

[ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment

Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning

Automated Deep Learning: Neural Architecture Search Is Not the End (a curated list of AutoDL resources and an in-depth analysis)

[UNMAINTAINED] Automated machine learning for analytics & production

A framework for large scale recommendation algorithms.

Merlion: A Machine Learning Framework for Time Series Intelligence

Automatic architecture search and hyperparameter optimization for PyTorch