MLA-C01 ML Model Development Practice Question
A data scientist is using SageMaker Experiments to track multiple training runs. They want to compare runs based on the objective metric and visualize performance. Which THREE steps should they perform? (Choose THREE.)
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
✓
Use SageMaker Studio Experiments UI to list and compare trials
To track and compare runs, you create an experiment, log parameters and metrics, and then use the Experiments UI or SDK to list and compare trials.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Deploy the best model to an endpoint
Why it's wrong here
Deployment is not needed for comparison.
- ✓
Use SageMaker Studio Experiments UI to list and compare trials
Why this is correct
The UI provides visualization and comparison.
- ✓
Log hyperparameters and metrics using the SageMaker SDK
Why this is correct
Logging is essential for tracking.
- ✓
Create a SageMaker Experiment
Why this is correct
An experiment is a logical grouping of related trials.
- ✗
Enable SageMaker Model Monitor for each run
Why it's wrong here
Model Monitor is for inference, not training runs.
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