Instruction: Discuss the common challenges faced when deploying machine learning models and how to overcome them.
Context: This question tests the candidate's practical experience and understanding of the full machine learning lifecycle, from development to deployment.
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The way I'd explain it in an interview is this: The challenges usually have less to do with training and more to do with integration, observability, drift, feature parity, latency, rollback, and ownership. A model can look great in experimentation and still fail because the live features...