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

Fast and Accurate ML in 3 Lines of Code

Automated Machine Learning with scikit-learn

An open source python library for automated feature engineering

ZenML 🙏: The bridge between ML and Ops. https://zenml.io.

Differentiable architecture search for convolutional and recurrent networks

Lightning ⚡️ fast forecasting with statistical and econometric models.

Merlion: A Machine Learning Framework for Time Series Intelligence

a delightful machine learning tool that allows you to train, test, and use models without writing code

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

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

A Hyperparameter Tuning Library for Keras

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

Automatic architecture search and hyperparameter optimization for PyTorch

High-Performance Symbolic Regression in Python and Julia

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

Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models