ML-Monitoring (EN)

Concept

Monitoring of ML models in production to measure performance

ML-Monitoring Architecture

flowchart TD     A[Production data] --> B[Data collection]     B --> C[Metric calculation]     C --> D[Model performance]     C --> E[Data quality]     C --> F[Resource usage]     D --> G[Dashboard/Notification]     E --> G     F --> G     G --> H[Automatic correction]     H --> I[Model updates]     I --> D

In Context

  • Typically used together with MLOps, CI/CD for ML and Model Governance
  • Related to: Model Drift, A/B Testing, Data Validation
  • Example use case: Monitoring a recommendation system in e-commerce to detect seasonal patterns
Quelle: AI Generated