EpistasisLab/tpot

Health v2 · maintenance only

Adoption not part of the score

10052 stars · 1563 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

TPOT (Tree-based Pipeline Optimization Tool) is a Python automated machine learning library that optimizes scikit-learn machine learning pipelines using genetic programming. It automates pipeline construction, feature selection, model selection, and hyperparameter tuning through evolutionary search.

Use cases

• automatically find the best machine learning pipeline for my dataset
• automate hyperparameter tuning and model selection
• use genetic programming to optimize an sklearn pipeline
• autoML for feature selection and preprocessing
• compare models and pipelines without manual tuning
• evolve a classification or regression pipeline automatically

When to choose

• you want automated pipeline search over scikit-learn estimators
• you need multi-objective or customizable evolutionary AutoML
• you want feature selection and preprocessing optimized together with model choice

When to avoid

• you need deep learning or LLM pipeline optimization
• you want a simple grid search rather than evolutionary optimization
• your data is too large for repeated cross-validation fits during search

Facets

library · maturity active

machine-learning data-science etl machine-learning data-science python cross-platform automl genetic-programming hyperparameter-optimization scikit-learn pipeline-optimization evolutionary-computation feature-engineering automation

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