Location data, for example about the proximity of a person or place to other points of interest, can improve the quality of several ML models (e.g. for search, recommendation). However, few tools make it easy for model developers to access, wrangle, and engineer location-based features. In this post, Anne Cocos (Director of Data Science at Iggy, an Amplify portfolio company) describes how to use the Iggy API within a Python script to augment a model designed to predict the sales price of homes with neighborhood intelligence. She shows how Iggy’s modules allow data scientists to easily add geospatial features to their model without using spatial joins or other specialized location-based queries.