Instruction: Discuss the methodologies and technologies you would use to detect anomalies in model performance over time.
Context: This question assesses the candidate's ability to identify and implement anomaly detection techniques for monitoring model performance, crucial for maintaining the reliability of ML systems in production.
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I would implement anomaly detection over a layered set of signals: prediction distributions, feature drift metrics, latency changes, calibration shifts, and delayed-label quality metrics when available. The goal is to detect patterns that look abnormal relative to the model's known...