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ebook

The Big Book of ML Monitoring

A comprehensive introduction to ML monitoring, including a framework to organize ML monitoring metrics and steps to take when dealing with data drift in production.

The big book of ML monitoring

No ML model lasts forever. To operate it successfully, you need a real-time view of its performance. Does it work as expected? What is causing the change? Is it time to intervene? This sort of visibility is not a nice-to-have, but a critical part of the model development lifecycle. Here comes ML monitoring.

Download the Big Book of ML Monitoring to learn:

  • How ML monitoring differs from software monitoring,
  • How to organize ML monitoring metrics in a single framework,
  • What is the difference between data and concept drift,
  • How to handle data drift in production.
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