AWS Certified Machine Learning - Specialty MLS-C01 — Topic 1 Question 204

Question

A retail company uses a machine learning (ML) model for daily sales forecasting. The model has provided inaccurate results for the past 3 weeks. At the end of each day, an AWS Glue job consolidates the input data that is used for the forecasting with the actual daily sales data and the predictions of the model. The AWS Glue job stores the data in Amazon S3. The company's ML team determines that the inaccuracies are occurring because of a change in the value distributions of the model features. The ML team must implement a solution that will detect when this type of change occurs in the future. Which solution will meet these requirements with the LEAST amount of operational overhead?

Accepted Answer

Correct answer: A. The correct answer is A. Option A: Use Amazon SageMaker Model Monitor to create a data quality baseline. Confirm that the emit_metrics option is set to Enabled in the baseline constraints file. Set up an Amazon CloudWatch alarm for the metric. Amazon SageMaker builds, trains and deploys machine learning models in a fully managed service. Amazon CloudWatch collects metrics, logs and alarms to monitor and react to operational health.

AWS Certified Machine Learning - Specialty MLS-C01 — Question 204