GLOSSARY TERM
What is Model Drift?
The decay of a machine learning model's predictive power due to changes in the real-world environment.
As operational environments shift, models must be monitored for drift. If detected, MLOps pipelines automatically trigger retraining using freshly mobilized data to restore accuracy.
Monitor for Model Drift
Implement continuous monitoring to ensure your AI models never degrade.