Driver ranking
Making a prediction using a linear regression model is a common use case in ML. This model predicts if a driver will complete a trip based on features ingested into Feast.
In this example, you'll learn how to use some of the key functionality in Feast. The tutorial runs in both local mode and on the Google Cloud Platform (GCP). For GCP, you must have access to a GCP project already, including read and write permissions to BigQuery.
This tutorial guides you on how to use Feast with Scikit-learn. You will learn how to:
  • Train a model locally (on your laptop) using data from BigQuery
  • Test the model for online inference using SQLite (for fast iteration)
  • Test the model for online inference using Firestore (for production use)
Try it and let us know what you think!
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