automated-feature-engineering

An open source python library for automated feature engineering

A curated list of automated machine learning papers, articles, tutorials, slides and projects

A list of high-quality (newest) AutoML works and lightweight models including 1.) Neural Architecture Search, 2.) Lightweight Structures, 3.) Model Compression, Quantization and Acceleration, 4.) Hyperparameter Optimization, 5.) Automated Feature Engineering.

Linear Prediction Model with Automated Feature Engineering and Selection Capabilities

Data search & enrichment library for Machine Learning → Easily find and add relevant features to your ML & AI pipeline from hundreds of public and premium external data sources, including open & commercial LLMs

The source code and dataset are used to demonstrate the DF model, and reproduce the results of the ACM CCS2018 paper

An open source python library for automated feature engineering based on Genetic Programming

A lightweight and visual AutoML system

A simplified version of featuretools for Spark

Predict the poverty of households in Costa Rica using automated feature engineering.

The project provides a complete end-to-end workflow for building a binary classifier in Python to recognize the risk of housing loan default. It includes methods like automated feature engineering for connecting relational databases, comparison of different classifiers on imbalanced data, and hyperparameter tuning using Bayesian optimization.

The MLOps platform for innovators 🚀

Automated creation of EntitySets from relational data stored in SQL databases

A curated list of awesome automated machine learning resources

Featransform: Automated Feature Engineering for Machine Learning

Automated, interpretable feature engineering using symbolic regression and genetic programming.

Predicting housing prices in Iowa using Python/Pandas/linear regression within SKLearn.