featuretools

A collection of demos showcasing automated feature engineering and machine learning in diverse use cases

Use advanced feature engineering strategies and select best features from your data set with a single line of code.

An R interface to the Python module Featuretools

A simplified version of featuretools for Spark

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

Exemplary, annotated machine learning pipeline for any tabular data problem.

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.

An add-on for Alteryx open source that automatically checks for the latest updates and warnings you when an Alteryx package is out of date.

Automl with Featuretools generate features and use tpot to select model

Files and Notebooks for Kaggle Titanic

Kaggle competition

Automated approach from feature engineering to modeling on the Kaggle Home Credit Default Risk competition dataset

Portfolio of data science projects completed by me for academic, self learning, and hobby purposes.

berserkr converts retailer data and performs machine learning modeling at scale