Feature Engineering Python Packages

feature-engine

Feature engineering and selection open-source Python library compatible with sklearn.

featuretools

An open source python library for automated feature engineering

sf-hamilton

Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.

upgini

Intelligent data search & enrichment for Machine Learning

nni

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

tsfel

An intuitive library to extract features from time series.

tpot

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

autots

Automated Time Series Forecasting

tsflex

Flexible time series feature extraction & processing

sf-hamilton-sdk

Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.

divik

Divisive Intelligent K-Means algorithm (DiviK) for joint feature selection and clustering of heavily multidimensional data.

apache-hamilton

Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.

evalml

EvalML is an AutoML library written in python.

sf-hamilton-ui

Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.

arfs

All Relevant Feature Selection

sf-hamilton-lsp

Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.

featurewiz

Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshadri. Collaborators welcome.

mljar-supervised

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

pixeltable

Data Infrastructure providing a declarative, incremental approach for multimodal AI workloads.

aligned

The DBT of ML, as Aligned describes data dependencies in ML systems, and reduce technical data debt

nvtabular

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.

fastcan

A fast canonical-correlation-based search algorithm for feature selection, system identification, data pruning, etc.

feathub-nightly

A stream-batch unified feature store for real-time machine learning

hyperactive

A unified interface for optimization algorithms and experiments