AWS Certified Machine Learning Engineer – Associate (MLA-C01) — Question 67

A company's ML engineer has deployed an ML model for sentiment analysis to an Amazon SageMaker endpoint. The ML engineer needs to explain to company stakeholders how the model makes predictions.
Which solution will provide an explanation for the model's predictions?

Answer options

• A. Use SageMaker Model Monitor on the deployed model.
• B. Use SageMaker Clarify on the deployed model.
• C. Show the distribution of inferences from A/В testing in Amazon CloudWatch.
• D. Add a shadow endpoint. Analyze prediction differences on samples.

Correct answer: B

Explanation

The correct answer is B, as SageMaker Clarify is specifically designed to provide insights into model predictions, including bias detection and explanations. Option A, SageMaker Model Monitor, focuses on monitoring model performance rather than explaining predictions. Option C provides statistical insights but lacks interpretability regarding how predictions are made, and Option D, while useful for performance comparison, does not directly explain the prediction mechanism.