Conf42: Machine Learning 2022

How to detect silent failures in ML models

The objective of the talk is to build understanding on why and how you need to monitor ML in production. We'll cover the taxonomy of failures based on use cases, data, characteristics of systems they interact with, and human involvement. You'll learn the tools (both statistical and algorithmic) used in dealing with these failures, their applications, and their limits. Fact is, the world changes...