Syllaro Academy

AWS Certified AI Practitioner

Model and Business Metrics

How to measure whether a model works: the confusion matrix and the classification metrics built on it (accuracy, precision, recall, F1, AUC), regression metrics (RMSE, MAE), and the business metrics that decide whether it was worth building.

Intermediate 22 minutes 4 Learning Objectives
  1. Read a confusion matrix and define true/false positives and negatives
  2. Define accuracy, precision, recall, and F1, and explain why accuracy alone misleads on imbalanced data
  3. Explain the precision-recall trade-off and when each matters more
  4. Distinguish classification metrics, regression metrics (RMSE, MAE), and business metrics (ROI, cost per user)