Model Monitoring and Drift Detection: Ensuring the Health and Fairness of Deployed Models

Discover essential strategies for maintaining the health and fairness of deployed models in this webinar on model monitoring in the MathWorks Modelscape solution. Key aspects such as fairness metrics, model drift detection, and resource management are addressed, showing you how to build dashboards and set up automated systems for optimal, unbiased model performance.

The webinar can be divided into the following sections:

• Introduction: The importance of model monitoring in ML deployments
• Key Components: Fairness metrics, model drift detection
• Dashboard Creation: Performance tracking, data drift, and resource use
• Automated Alerts: Gathering user feedback and stakeholder alerts