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Shedding Light On Silent Model Failures With NannyML
Sept. 14, 2022, 2 a.m. | Tobias Macey
The Machine Learning Podcast www.themachinelearningpodcast.com
Summary
Because machine learning models are constantly interacting with inputs from the real world they are subject to a wide variety of failures. The most commonly discussed error condition is concept drift, but there are numerous other ways that things can go wrong. In this episode Wojtek Kuberski explains how NannyML is designed to compare the predicted performance of your model against its actual behavior to identify silent failures and provide context to allow you to determine whether and how …
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