Instruction: Discuss the strategies and tools you recommend for managing version control of both ML models and their associated datasets in production environments.
Context: This question evaluates the candidate's approach to ensuring traceability and manageability of ML components through version control, a fundamental practice in MLOps for maintaining and iterating on production systems.
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The way I'd approach it in an interview is this: I separate concerns but connect lineage. Code belongs in standard version control, while models and datasets need artifact and data versioning systems that can handle size, metadata, and reproducibility....
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