AWS Certified Machine Learning – Specialty — Question 346

A company deployed a machine learning (ML) model on the company website to predict real estate prices. Several months after deployment, an ML engineer notices that the accuracy of the model has gradually decreased.

The ML engineer needs to improve the accuracy of the model. The engineer also needs to receive notifications for any future performance issues.

Which solution will meet these requirements?

Answer options

• A. Perform incremental training to update the model. Activate Amazon SageMaker Model Monitor to detect model performance issues and to send notifications.
• B. Use Amazon SageMaker Model Governance. Configure Model Governance to automatically adjust model hyperparameters. Create a performance threshold alarm in Amazon CloudWatch to send notifications.
• C. Use Amazon SageMaker Debugger with appropriate thresholds. Configure Debugger to send Amazon CloudWatch alarms to alert the team. Retrain the model by using only data from the previous several months.
• D. Use only data from the previous several months to perform incremental training to update the model. Use Amazon SageMaker Model Monitor to detect model performance issues and to send notifications.

Correct answer: A

Explanation

To address accuracy degradation (model drift), incremental training should be used to update the model with new data without discarding previous training progress. Amazon SageMaker Model Monitor is the appropriate service for continuously tracking production model quality and generating alerts when performance deviates from a baseline. Restricting training data to only the last few months would discard valuable historical data, and SageMaker Debugger is intended for monitoring training jobs rather than production endpoints.