MLS-C01 Modeling Practice Question
A company uses Amazon SageMaker to train a model and wants to track metrics like loss and accuracy in real-time. Which SageMaker feature should be used?
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
✓
SageMaker metrics and CloudWatch dashboards
SageMaker's built-in metrics integration with CloudWatch allows real-time tracking of training metrics such as loss and accuracy. Option A (SageMaker Model Monitor) is for monitoring inference quality and data drift after deployment, not real-time training metrics. Option C (SageMaker Experiments) is for organizing, tracking, and comparing different experiment runs, but it does not provide real-time streaming of metrics during training. Option D (SageMaker Debugger) is used for debugging training issues like gradient anomalies, not for real-time metric tracking.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
SageMaker Model Monitor
Why it's wrong here
For inference monitoring.
- ✓
SageMaker metrics and CloudWatch dashboards
Why this is correct
Provides real-time training metrics.
- ✗
SageMaker Experiments
Why it's wrong here
For organizing trials.
- ✗
SageMaker Debugger
Why it's wrong here
For debugging training issues.
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