Data Drift & Concept Drift Detection in Production ML: MLOps and Production AI Guide (2026)

Data Drift & Concept Drift Detection in Production ML in MLOps and Production AI

Intermediate Topic 2 of 9

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.

Monitoring, Logging & Observability in MLOps Building Real-Time Monitoring Dashboards for ML Systems

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