There are 36 repositories under feature-engineering topic.
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
Feature Store for Machine Learning
Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.
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
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
[UNMAINTAINED] Automated machine learning for analytics & production
OpenMLDB is an open-source machine learning database that provides a feature platform enabling consistent features for training and inference.
A low code Machine Learning service that personalizes articles, listings, search results, recommendations to boost user engagement. A friendly Learn-to-Rank engine
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
Automated Deep Learning without ANY human intervention. 1'st Solution for AutoDL challenge@NeurIPS.
Feature engineering package with sklearn like functionality
A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.
Feathr – An Enterprise-Grade, High Performance Feature Store
Kaggle：Quora Question Pairs, 4th/3396 (https://www.kaggle.com/c/quora-question-pairs)
Feature exploration for supervised learning
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.
Code for Kaggle Data Science Competitions
Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
Deep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders.
Features selector based on the self selected-algorithm, loss function and validation method
An intuitive library to extract features from time series.
Automated Time Series Forecasting
A scalable general purpose micro-framework for defining dataflows. You can use it to create dataframes, numpy matrices, python objects, ML models, etc.
A curated list of resources dedicated to Feature Engineering Techniques for Machine Learning
EvalML is an AutoML library written in python.
FIBO Rule - 实时AI智能决策引擎、规则引擎、风控引擎、数据流引擎。 通过可视化界面进行规则配置，无需繁琐开发，节约人力，提升效率，实时监控，减少错误率，随时调整； 支持规则集、评分卡、决策树，名单库管理、机器学习模型、三方数据接入、定制化开发等；
A collection of demos showcasing automated feature engineering and machine learning in diverse use cases
DeltaPy - Tabular Data Augmentation (by @firmai)
Open solution to the Home Credit Default Risk challenge :house_with_garden:
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.
A machine learning preprocessing library over batch data, providing performant and Pandas-style easy-to-use API for model development