Detecting and Handling Model Drift
Learn how to detect when a deployed AI model's performance degrades over time and how to respond with retraining, alerts, and rollbacks.
What Is Model Drift
Model drift is the gradual decline in a deployed model's quality as the real world changes away from its training data.
Data Drift vs Concept Drift
Data drift: inputs change distribution. Concept drift: the relationship between inputs and the correct answer changes.
All lessons in this course
- Model Versioning & Experiment Tracking
- A/B Testing AI Models
- Monitoring Model Performance
- Detecting and Handling Model Drift