Submissions for MLOps November edition

On ML workflows, tools, automation and running ML in production

Gaetan Castelein


Using feature stores to build a fraud model

Submitted Jun 2, 2021

Feature stores enable companies to make the difficult leap from research to production machine learning. At their best, feature stores allow you to define new features, automate the data pipelines to process feature values, and serve data for training and online inference. You can quickly and reliably serve features to your production models so your customers aren’t waiting for predictions.

In this talk, we’ll walk through a common use case for feature stores, developing and fielding a fraud model. We’ll show you source code and walk you through the entire lifecycle from building new features to serving online data.


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