6. Deployment

Monitoring — Quiz

Test your understanding of monitoring with 5 practice questions.

Practice Questions

Question 1

Which of the following statistical tests is most appropriate for detecting significant differences in the distribution of a continuous input feature between training and production data, indicating data drift?

Question 2

When monitoring a machine learning model, what is the primary purpose of a 'canary deployment' strategy in conjunction with A/B testing?

Question 3

A machine learning model's performance is degrading over time, and analysis reveals that the relationship between a specific input feature and the target variable has changed. Which type of drift is primarily responsible for this degradation?

Question 4

Consider a classification model where the class distribution in production data has significantly shifted compared to the training data. For example, a fraud detection model trained on a 1:100 fraud-to-non-fraud ratio now sees a 1:10 ratio. Which metric would be most immediately impacted and require careful monitoring?

Question 5

In a real-time model monitoring system, what is the most effective strategy to minimize 'alert fatigue' while ensuring critical issues are promptly addressed?