Instruction: Explain how anomaly detection techniques can be applied to identify issues in ML model performance in real-time.
Context: This question probes the candidate's ability to implement anomaly detection for proactive model performance monitoring.
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I would use anomaly detection to catch unusual patterns in model inputs, outputs, error rates, feature distributions, and operational metrics before a human notices obvious business damage. It is particularly useful when the system has too many signals for manual thresholding...