hardMultiple ChoiceObjective-mapped
MLA-C01 Practice Question: A machine learning engineer is using SageMaker…
A machine learning engineer is using SageMaker Automatic Model Tuning (AMT) to optimize hyperparameters for a random forest model. The engineer notices that the tuning job is taking too long and many hyperparameter combinations are being evaluated but not improving the objective metric. Which action should the engineer take to make the tuning more efficient?
⚠ Common exam trap
Test-takers frequently confuse early stopping with reducing instance size or changing search strategies, not realizing that early stopping directly addresses wasted computation on poor trials without sacrificing search quality.
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
✓
Enable early stopping for the tuning job
Enabling early stopping in SageMaker Automatic Model Tuning (AMT) terminates poorly performing training jobs before they complete, which reduces wasted compute time and speeds up the tuning process. This is especially effective when using Bayesian optimization, as it allows the algorithm to focus on promising hyperparameter regions and avoid evaluating combinations that are unlikely to improve the objective metric.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Switch the strategy from Bayesian to random search
Why it's wrong here
Random search does not exploit previous results to focus on promising regions.
- ✗
Use a smaller instance type for each training job
Why it's wrong here
Smaller instances may take longer per trial, not improving efficiency.
- ✗
Increase the maximum number of training jobs
Why it's wrong here
More jobs increase total time, not efficiency.
- ✓
Enable early stopping for the tuning job
Why this is correct
Early stops poorly performing trials, reducing wasted computation.
Go deeper
Related to this question
About these practice questions
One of 835 original MLA-C01 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
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.