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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.

PreviousSample use-case tutorialsNextFraud detection on GCP

Last updated 2 years ago

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 . You will learn how to:

  • Train a model locally (on your laptop) using data from

  • Test the model for online inference using (for fast iteration)

  • Test the model for online inference using (for production use)

Try it and let us know what you think!

Driver Ranking Example
Scikit-learn
BigQuery
SQLite
Firestore
Run in Google Colab
View Source in Github