Monitoring Performance of AI/ML Models focuses on tracking, evaluating, and maintaining the accuracy and reliability of machine learning systems in production environments. Continuous monitoring helps organizations detect performance issues, data drift, and model degradation over time. This training explains how to measure model accuracy, latency, precision, recall, and other evaluation metrics. It also covers anomaly detection, retraining strategies, monitoring dashboards, alerting mechanisms, and model governance techniques. You will learn how organizations ensure stable and efficient AI operations across real-world applications. The course also highlights best practices for building scalable, reliable, and high-performing AI/ML monitoring systems.
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