Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning

MIT License

AutoML-Implementation-for-Static-and-Dynamic-Data-Analytics

Automated Machine Learning with scikit-learn

BSD 3-Clause "New" or "Revised" License

auto-sklearn

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

mljar-supervised

The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.

Apache License 2.0

Neuraxle

AutoGluon: AutoML for Image, Text, Time Series, and Tabular Data

autogluon

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

Other

SMAC3