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Prioritize the most promising directions for an AI project

Diagnose errors in a machine learning system

Build ML in complex settings, such as mismatched training/test sets

Set up an ML project to compare to and/or surpass human-level performance

Know when and how to apply end-to-end learning, transfer learning, and multi-task learning.

Define human-level performance