Learn Model Monitoring in DataRobot by understanding how to continuously track and evaluate machine learning models in production environments. This training covers how to monitor model performance metrics such as accuracy, precision, and recall over time. It also explains how to detect data drift, concept drift, and prediction anomalies using built-in monitoring dashboards. You will learn how to set up alerts, analyze logs, and compare training and real-time data to ensure model stability. The course focuses on maintaining reliable, high-performing models through continuous observation and proactive issue detection in production systems.
Showing the single result
