Fraud detection on GCP

A common use case in machine learning, this tutorial is an end-to-end, production-ready fraud prediction system. It predicts in real-time whether a transaction made by a user is fraudulent.

Throughout this tutorial, we’ll walk through the creation of a production-ready fraud prediction system. A prediction is made in real-time as the user makes the transaction, so we need to be able to generate a prediction at low latency.

Fraud Detection Example

Our end-to-end example will perform the following workflows:

• Computing and backfilling feature data from raw data

• Building point-in-time correct training datasets from feature data and training a model

• Making online predictions from feature data

Here's a high-level picture of our system architecture on Google Cloud Platform (GCP):

Run in Google Colab

View Source on Github