Features API - Data Science Guides

This page includes examples of Features API usage in various data science applications. It is recommended to have familiarised yourself with the Features API basic usage and documentation first. The pages below include links to download and run the content as Jupyter notebooks:

  • Features API usage and examples - Contains examples on how to request features and their associated stats, and how to begin exploring them.

  • Feature engineering guide - The Feature Engineering Guide notebook helps data science teams understand and get hands-on experience querying different event-based features from PredictHQ's Features API. This guide outlines, with clear and simple examples, recommended features per event category. Data science teams can use these examples to create features easily and include them in their own demand forecasting models or any other applicable models.

  • Demand surge alerts - Demand surges reflect when many events are occurring on the same day or days reflect a spike in event activity that is beyond the normal amount of demand for a location. This notebook showcases how Features API can be used to scan for potential demand surges in a future time period.