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MLS-C01 Modeling Practice Question

A company wants to use Amazon SageMaker to automatically tune hyperparameters for a XGBoost model. Which built-in 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 Automatic Model Tuning

SageMaker Automatic Model Tuning performs hyperparameter optimization. Option A (SageMaker Debugger) monitors training. Option B (SageMaker Model Monitor) detects drift. Option C (SageMaker Experiments) tracks trials. Option D (SageMaker Automatic Model Tuning) correctly performs hyperparameter tuning.

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 Debugger

    Why it's wrong here

    Debugger monitors training, not tunes.

  • SageMaker Model Monitor

    Why it's wrong here

    Model Monitor detects data drift, not hyperparameter tuning.

  • SageMaker Experiments

    Why it's wrong here

    Experiments track and compare runs, not tune.

  • SageMaker Automatic Model Tuning

    Why this is correct

    This is the service for hyperparameter tuning.

About these practice questions

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JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This MLS-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 MLS-C01 exam.