Which AWS service provides fully automated model tuning?
Short answer
B Amazon SageMaker
Question
Key Takeaways
The question tests knowledge of AWS ML services and their automation capabilities; the trap is confusing purpose-built AI services like Personalize or Comprehend with SageMaker's full ML workflow automation.
For fully automated model tuning, Amazon SageMaker is the correct choice, offering SageMaker Autopilot and hyperparameter optimization. Community consensus strongly supports SageMaker as the managed ML service that automates model building and tuning.
Common mistake: Choosing Amazon Personalize, because it may appear to build and tune recommendation models automatically, but it is a domain-specific service for personalization, not a general-purpose ML model tuning service.
Expert Analysis
Why the Answer Is Correct
Amazon SageMaker is a fully managed service designed for building, training, and deploying machine learning models. It includes SageMaker Autopilot, which automatically explores candidate models, performs feature engineering, and tunes hyperparameters. SageMaker also offers automatic model tuning (hyperparameter optimization) that searches for the best model configuration without manual intervention.
Why the Other Options Are Wrong
Amazon Personalize is a specialized service for building recommendation systems, not a general-purpose ML model tuning service. Amazon Comprehend is an NLP service that extracts insights from text, not for training custom models. Amazon Athena is an interactive query service for analyzing data in S3, unrelated to model tuning.
Community Comment Notes
Community comments [1] and [2] both correctly identify Amazon SageMaker as the answer, mentioning SageMaker Autopilot and SageMaker Hyperparameter Optimization as key features. Comment [3] further explains that Autopilot automates the ML model development process, making it ideal for fully automated model tuning. The unanimous vote distribution (100% B) reinforces that this is a clear-cut question for candidates familiar with SageMaker's capabilities.
Official Reference
- https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot.html
- https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning.html
These links open the official vendor documentation in a new tab.
Exam Strategy
Identify the key phrase 'fully automated model tuning' — Amazon SageMaker Autopilot is the only option that provides end-to-end automation of model tuning. Eliminate services with narrower scopes (Personalize, Comprehend) and data query services (Athena) to quickly arrive at the correct answer.
Community Votes
100% of anonymous learners picked answer B. Votes are pick records left by other test-takers — they are not the verified answer.
Discussion 3 contributions
Compiled from public community threads and reader submissions, lightly edited for clarity. Handles and vote tallies are shown as recorded, and comments reflect the views of individual contributors.
From public community threads 3
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aws_Tamilan 👍 1 Answered BB. Amazon SageMaker Explanation: Amazon SageMaker is a fully managed service that provides tools to build, train, and deploy machine learning models. It includes SageMaker Autopilot, which automates the machine learning model development process, including model tuning. This feature helps users create and optimize models with minimal manual intervention, making it ideal for fully automated model tuning.
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may2021_r 👍 1 Answered BThe correct answer is B. Amazon SageMaker provides fully automated model tuning capabilities through its hyperparameter optimization features.
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Jessiii 👍 1 Answered BOffers automatic model tuning through SageMaker Autopilot and SageMaker Hyperparameter Optimization, providing fully automated model tuning.
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