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Libraries and platforms that turn raw data into machine-learning-ready features — automated generation, synthesis, and selection.

Feature Engineering Tools

A working list of tools and libraries for automated feature engineering — generating, synthesizing, and selecting the features that feed machine learning models.

01

Featuretools

An open source Python framework for automated feature engineering, built around Deep Feature Synthesis.

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03

autofeat

Linear prediction models with automated feature engineering and selection capabilities.

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04

tsfresh

A Python package that automatically calculates a large number of time series characteristics, the so-called features.

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05

Explorium

Automated feature engineering that intelligently extracts features from raw data sources to feed machine learning projects.

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06

Feature-engine

A Python library with multiple transformers to engineer and select features for use in machine learning models.

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08

PyFeat

A Python-based effective feature generation tool from DNA, RNA, and protein sequences.

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09

featurewiz

A Python library for creating and selecting the best features in your data set fast, powered by the MRMR algorithm.

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