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MLOps Academy · Lesson

The Four Pillars of ML Observability

Data, model, drift, and explainability together.

Beyond Plain Monitoring

Monitoring tells you a service is up. Observability lets you ask why a model behaves the way it does, even for questions you did not plan for. 🔍

The Four Pillars

ML observability rests on four pillars: the data going in, the model and its predictions, drift over time, and explainability of each output.

All lessons in this course

  1. The Four Pillars of ML Observability
  2. Log Predictions for Later Analysis
  3. Slice Metrics by Segment and Cohort
  4. Explain Predictions with SHAP
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