feature-engineering

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

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

An open source python library for automated feature engineering

Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.

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

📖 [译] 面向机器学习的特征工程

TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library for building modular, reusable, strongly typed machine learning workflows on Apache Spark with minimal hand-tuning

A low code Machine Learning peersonalized ranking service for articles, listings, search results, recommendations that boosts user engagement. A friendly Learn-to-Rank engine

[UNMAINTAINED] Automated machine learning for analytics & production

Feathr – An Enterprise-Grade, High Performance Feature Store

Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.

OpenMLDB is an open-source machine learning database that provides a feature platform computing consistent features for training and inference.

Feature engineering package with sklearn like functionality

The Virtual Feature Store. Turn your existing data infrastructure into a feature store.

Automated Deep Learning without ANY human intervention. 1'st Solution for AutoDL challenge@NeurIPS.

A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.

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.

Hopsworks - Data-Intensive AI platform with a Feature Store

LAMA - automatic model creation framework

A scalable general purpose micro-framework for defining dataflows. You can use it to build dataframes, numpy matrices, python objects, ML models, etc. Embed Hamilton anywhere python runs, e.g. spark, airflow, jupyter, fastapi, python scripts, etc.