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Automated Machine Learning (AutoML) Tools: Open-source Libraries & Platforms

AutoML tools — open-source libraries and cloud platforms that automate model selection, feature engineering and tuning.

25 topics•3 categories•Updated October 2026

Open-source AutoML Libraries

14 entries

Libraries you can run yourself.

01Auto-WEKAAuto-WEKA simultaneously selects a learning algorithm and sets its hyperparameters using Bayesian optimization. 02auto-sklearnauto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. 03TPOTTPOT is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming. 04H2O AutoMLH2O AutoML automates algorithm selection, feature generation, hyperparameter tuning, iterative modeling, and model assessment. 05TransmogrifAITransmogrifAI is an AutoML library written in Scala that runs on top of Apache Spark. 06MLBoxMLBox is a powerful Automated Machine Learning python library. Last commit on the default branch was in August 2020, so treat it as legacy. 07AutoKerasAutoKeras is an AutoML system based on Keras. The goal of AutoKeras is to make machine learning accessible to everyone. 08AutoGluonAutoGluon: AutoML for Text, Image, and Tabular Data. 09Auto-PyTorchAuto-PyTorch optimizes the network architecture and the training hyperparameters to enable fully automated deep learning (AutoDL). Last commit on the default branch was in August 2022. 10PyCaret AutoMLThis function returns the best model out of all models created in the current active environment based on the metric defined in the optimize parameter. 11FLAMLLightweight Python library from Microsoft for fast, economical automated machine learning and hyperparameter tuning. 12LudwigDeclarative deep learning framework that builds models from a configuration file. 13EvalMLAutoML library for building, optimizing and evaluating machine learning pipelines. 14MLJAR AutoMLAutoML tool and hosted platform from MLJAR.

Cloud & Commercial AutoML

6 entries

Managed AutoML services.

Related Pages

5 entries

Neighbouring pages on this site.

Frequently Asked Questions

What is AutoML?

AutoML automates parts of the machine learning workflow, such as feature engineering, model selection and hyperparameter tuning, so that models can be built faster and with less manual effort.

Which AutoML library should I start with?

auto-sklearn and TPOT work on tabular data with scikit-learn, AutoGluon and FLAML are strong general-purpose choices, and PyCaret offers a low-code workflow.

Which projects are no longer active?

MLBox's last commit was in 2020 and Auto-PyTorch's in 2022, so prefer more actively maintained libraries for new projects.

How current is this page?

Links were checked in October 2026. Sites that block automated checks are kept and may need a manual click. Last-commit dates come from GitHub in October 2026 and show default-branch activity only; check each project's release notes before adopting it.