What are the best practices for monitoring machine learning models?

What are the best practices for monitoring machine learning models?

The best practices for monitoring ML models include setting clear performance metrics, tracking data drift, and implementing alert systems.

How do I track data drift effectively?

You can track data drift by comparing the statistical properties of incoming data against the training data using techniques like Kolmogorov-Smirnov tests.

What metrics should I focus on for model performance?

Focus on metrics like accuracy, precision, recall, F1 score, and AUC-ROC, depending on your specific use case.

Can you explain how to set up an alert system?

To set up an alert system, define thresholds for your performance metrics and use monitoring tools to send notifications when these thresholds are breached.