When data leakage turns into a flood of trouble

Rajiv Shah teaches Daniel and Chris about data leakage, and its major impact upon machine learning models. It’s the kind of topic that we don’t often think about, but which can ruin our results. Raj discusses how to use activation maps and image embedding to find leakage, so that leaking information in our test set does not find its way into our training set.

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Featuring:

• Rajiv Shah – Twitter, GitHub, LinkedIn, Website
• Chris Benson – Twitter, GitHub, LinkedIn, Website
• Daniel Whitenack – Twitter, GitHub, Website

Show Notes:

• Rajiv Shah | University of Illinois at Chicago
• Rajiv Shah | DataRobot Blog
• DataRobot

Something missing or broken? PRs welcome!