AWS Certified Machine Learning Engineer - Associate MLA-C01 — Topic 1 Question 133

Question

A medical company ingests streams of data from devices that monitor patients’ vital signs. The company uses Amazon SageMaker and plans to prepare ML models to predict adverse events for patients. The dataset is large with thousands of features. An ML engineer needs to run several hundred training iterations with different sets of features, different algorithms, and many potential parameters. The ML engineer must implement a solution to log the characteristics and results of each training iteration. Which solution will meet these requirements with the LEAST implementation effort?

Accepted Answer

Correct answer: D. The correct answer is D. Option D: Use SageMaker Experiments to track the characteristics and results of each iteration. Amazon SageMaker builds, trains and deploys machine learning models in a fully managed service.

AWS Certified Machine Learning Engineer - Associate MLA-C01 — Question 133