Data Drift & Concept Drift Detection in Production ML
Understanding Drift in Machine Learning
Over time, real-world data changes. These changes can silently reduce model accuracy. Drift detection helps maintain long-term reliability.
Types of Drift
- Data Drift: Input feature distribution changes
- Concept Drift: Relationship between inputs and outputs changes
Automated drift monitoring ensures proactive retraining and stable AI systems.
