Automated Retraining Triggers Quiz

What you'll be asked

1. Which of the following is the most common reason to trigger an automated retraining pipeline for a machine learning model?
2. When monitoring a model in production, which metric is most useful for triggering a retraining pipeline when 'concept drift' is suspected?
3. Why is it dangerous to rely solely on a time-based schedule (e.g., retraining every Monday) for model updates?
4. You observe that the distribution of a key input feature has shifted significantly, but the model's accuracy remains stable. What is the most appropriate next step?
5. In a production environment, you implement a 'Champion-Challenger' (A/B testing) framework for retraining. What is the primary benefit of this strategy compared to a direct replacement trigger?

Answers and explanations come after you submit.