Question 8
Domain 1: Fundamentals of AI and MLWhich AWS service is best suited for automating the process of identifying the best hyperparameters for a model?
Correct answer: A
Explanation
Amazon SageMaker Autopilot automates model tuning by running “automatic model tuning,” which AWS defines as the service for finding the best hyperparameter values. It is designed to “automatically explore different hyperparameter combinations” to optimize model performance, so it fits this task.
Why each option is right or wrong
A. Amazon SageMaker Autopilot
Amazon SageMaker Autopilot is the SageMaker feature that performs automatic model tuning, which AWS documents as the process of trying multiple hyperparameter combinations and selecting the best-performing one. In the SageMaker Automatic Model Tuning documentation, AWS states that tuning jobs can run multiple training jobs in parallel and optimize objective metrics by searching the hyperparameter space, so it directly matches a request to automate hyperparameter identification.
B. Amazon Comprehend
Amazon Comprehend is a natural language processing service for text analysis, not model hyperparameter tuning.
C. Amazon Polly
Amazon Polly converts text to lifelike speech; it does not train or tune ML models.
D. Amazon Transcribe
Amazon Transcribe converts speech to text; it is not used for hyperparameter optimization.