Automated Machine Learning: Deploying AutoML to the Cloud

This year may be the year that automated machine learning (AutoML) enters the data science vernacular. KDnuggets recently wrote a comprehensive review of the state of AutoML in 2017, AirBnB described how AutoML has accelerated their data scientists' productivity, and the International Conference on Machine Learning (ICML) hosted another workshop on AutoML in August. In this post, I share an AutoML setup to train and deploy pipelines in the cloud using Python, Flask, and two AutoML frameworks that automate feature engineering and model building. To jump straight to the code, check out the GitHub repository. AutoML is a broad term and technically could encompass the entire data science cycle from data exploration to model building.