Multiple Choice Flashcards on 02 Databricks Certified Machine Learning Profes...

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Flashcard Practice Databricks Certified Machine Learning Professional Multiple Choice

A company trains a deep learning model that takes several days to train, is expensive to reproduce, and uses data already available in a controlled training workspace. The serving and monitoring code still changes regularly. Which approach is most reasonable?

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Drop staging because resource-intensive training makes pre-production testing impractical. Retrain the model in each environment even when the artifact is unchanged and expensive. Use a hybrid artifact step while deploying serving code through CI/CD. Let data scientists manually copy the artifact into production and edit serving code there.

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