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How are production ML systems typically handling distribution shift over time? [D]
r/MachineLearning · 8h ago · 7 · workflow deployment monitoring

Practical discussion of production ML monitoring and retraining strategies for handling data drift, covering continuous retraining (interval vs trigger-based), drift detection, shadow models, and human-in-the-loop approaches. The post emphasizes that operational constraints often matter more than model architecture when choosing drift mitigation strategies.