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Compare Generative and Discriminative Modeling

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Problem

Compare generative modeling and discriminative modeling approaches

Asked in the phone_screen stage. Explain the distinction in learning objective and probability modeling, then discuss how the choice affects an end-to-end ML system. Cover representative model families, data and serving requirements, evaluation, scalability, and failure modes. Address when a hybrid design is appropriate, including training-serving skew, feature drift, latency, and monitoring.