I worked on building a python library for automated feature engineering called Featuretools (https://github.com/featuretools/featuretools/). I had been working on it for 2 years, but in 2017 we separated it from the rest of the codebase and made it open source.
Even though feature engineering is crucial for building machine learning pipelines, there are few formal methods for performing feature engineering. We see Featuretools filling a missing component in the software engineering stack for data science.
It has already been put to the test with our customers at my company, but we have also begun to release demos so that others can pick it up https://www.featuretools.com/demos.
Even though feature engineering is crucial for building machine learning pipelines, there are few formal methods for performing feature engineering. We see Featuretools filling a missing component in the software engineering stack for data science.
It has already been put to the test with our customers at my company, but we have also begun to release demos so that others can pick it up https://www.featuretools.com/demos.