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MLA-C01 Practice Question: A team wants to track and compare multiple…
A team wants to track and compare multiple machine learning experiments, including hyperparameters, metrics, and artifacts. They are using Amazon SageMaker. Which AWS service or feature should they use to achieve this?
⚠ Common exam trap
Watch out — candidates often confuse SageMaker Studio (the IDE) with SageMaker Experiments (the tracking service), assuming Studio alone provides experiment tracking, but Studio is merely the interface that can visualize experiment data stored by Experiments.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Amazon SageMaker Experiments
Amazon SageMaker Experiments is the correct service because it is specifically designed to track and compare machine learning experiments, including hyperparameters, metrics, and artifacts. It provides a structured way to log, organize, and analyze multiple runs, enabling teams to identify the best-performing model configurations.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
AWS CloudTrail
Why it's wrong here
CloudTrail logs API calls.
- ✓
Amazon SageMaker Experiments
Why this is correct
Experiments is the correct service for tracking.
- ✗
Amazon SageMaker Model Registry
Why it's wrong here
Model Registry manages model versions.
- ✗
Amazon SageMaker Studio
Why it's wrong here
Studio is an IDE, not experiment tracking.
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