AWS Certified Machine Learning Engineer – Associate (MLA-C01) — Question 151

A hospital is using an ML model to validate x-ray results. The hospital runs a nightly batch inference job. The hospital needs to produce a daily report about model data quality and model performance.

Which solution will meet these requirements?

Answer options

• A. Schedule a monitoring job in Amazon SageMaker Model Monitor. Generate the monitoring results for the model and data.
• B. Create an Amazon CloudWatch dashboard that includes the metrics for processing steps in the nightly batch inference job. Compare the baseline resource metrics. Share the dashboard link.
• C. Use AWS Glue DataBrew to create a custom recipe job that uses the Numerical Statistics data quality check for the model file. Generate the results.
• D. Create a SageMaker AI pipeline that includes a QualityCheck step to run monitoring jobs. Generate the monitoring results for the model and the data.

Correct answer: A

Explanation

The correct answer is A because Amazon SageMaker Model Monitor is specifically designed to monitor machine learning models and provide insights into data quality and model performance. The other options, while useful for different purposes, do not directly address the need for monitoring results related to the model and data quality as required by the hospital.