Adaptive Machine Learning Model Performance Monitoring Pipeline

Create a comprehensive monitoring system for machine learning model performance that automatically tracks prediction accuracy, detects concept drift, and triggers model retraining workflows. Implement statistical drift detection algorithms, integrate with model version control, and generate automated alerts when performance metrics deviate beyond predefined thresholds. Support multiple machine learning frameworks and include robust logging and telemetry.