A Full-Stack Machine Learning Environment for Rapidly Evolving Industry Applications

Abstract

Developing, deploying, and maintaining machine learning models is a key function of many data science teams. We describe a framework built by American Family Insurance to model the risk profiles of properties. Through empirical experiments, we demonstrate that our automated, end-to-end framework provides a rapid platform for experimentation and productionalization in a business environment.