Instruction: Describe the differences in lifecycle management between stateful and stateless ML models, including deployment and maintenance strategies.
Context: This question assesses the candidate's understanding of stateful and stateless architectures in ML models and their implications for lifecycle management.
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The way I'd approach it in an interview is this: Stateless models are easier to version and roll back because each request is independent of long-lived model state. Stateful models are more complex because predictions may depend on session history, user...