Question 1,235 of 1,672
MLS-C01 Modeling Practice Question
A team is using Amazon SageMaker to train a deep learning model for image classification. The training job is taking too long, and they want to reduce training time without sacrificing model accuracy. Which approach is most effective?
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 transfer learning with a pre-trained model and fine-tune on the target dataset
Transfer learning uses a pre-trained model that already has learned feature representations from a large dataset. Fine-tuning this model on the target dataset requires significantly less training time compared to training from scratch, while still achieving high accuracy. Option A is wrong because reducing batch size can slow down training and may cause convergence issues. Option B is wrong because reducing epochs can lead to underfitting and lower accuracy. Option C is wrong because reducing image resolution may remove important details, degrading model performance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Reduce the batch size
Why it's wrong here
Smaller batch sizes can increase training time due to more updates and slower convergence.
- ✗
Reduce the number of training epochs
Why it's wrong here
Reducing epochs may cause underfitting and reduce accuracy.
- ✗
Reduce the image resolution
Why it's wrong here
Reducing resolution may lose important details, harming accuracy.
- ✓
Use transfer learning with a pre-trained model and fine-tune on the target dataset
Why this is correct
Transfer learning uses features learned from a large dataset, allowing faster convergence and similar accuracy.
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Last reviewed: Jun 20, 2026
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.
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