hardMultiple ChoiceObjective-mapped
MLA-C01 Practice Question: A data scientist is using Amazon SageMaker…
A data scientist is using Amazon SageMaker Debugger to monitor training metrics. They want to stop training automatically if the model is overfitting. Which action should they take?
⚠ Common exam trap
Many exam-takers confuse monitoring for overfitting with monitoring for convergence or training stability, leading them to select a built-in rule (like vanishing gradients or loss plateau) that does not directly trigger a STOP action for overfitting.
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
✓
Configure a custom rule that triggers a STOP training action when validation loss stops decreasing
SageMaker Debugger allows you to define custom rules that can invoke a STOP training action when a specified condition is met, such as validation loss ceasing to decrease. This enables automatic termination of a training job to prevent overfitting, as the model is no longer improving on unseen data.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Define a Debugger rule that monitors the loss plateau
Why it's wrong here
A plateau rule can stop training when loss stops decreasing, but it does not specifically target overfitting; it stops based on convergence.
- ✓
Configure a custom rule that triggers a STOP training action when validation loss stops decreasing
Why this is correct
A custom rule can monitor validation loss and stop training when it plateaus or increases, indicating overfitting.
- ✗
Create a SageMaker Training Compiler
Why it's wrong here
Training Compiler optimizes model training but does not monitor or stop training based on overfitting.
- ✗
Use a built-in rule that checks for vanishing gradients
Why it's wrong here
Vanishing gradients are a different problem, not overfitting.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLA-C01 exam.