Question 661 of 1,672
MLS-C01 Modeling Practice Question
A data scientist is developing a deep learning model for object detection using Amazon SageMaker. The training dataset has 50,000 labeled images. The data scientist wants to improve model generalization without collecting more data. Which TWO techniques can be applied? (Choose two.)
⚠ Common exam trap
A common mix-up: candidates confuse techniques that improve training speed or convergence (like increasing learning rate or epochs) with those that improve generalization, failing to recognize that overfitting is the core issue when data is limited.
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
✓
Apply data augmentation techniques such as random cropping and horizontal flipping.
Data augmentation techniques like random cropping and horizontal flipping artificially expand the training dataset by generating modified versions of existing images. This exposes the model to more varied input patterns, reducing overfitting and improving generalization without requiring new labeled 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.
- ✗
Increase the learning rate to speed up convergence.
Why it's wrong here
Higher learning rate can cause instability and not improve generalization.
- ✗
Increase the number of training epochs to ensure convergence.
Why it's wrong here
More epochs can lead to overfitting, not generalization.
- ✓
Apply data augmentation techniques such as random cropping and horizontal flipping.
Why this is correct
Data augmentation increases data diversity without new data.
- ✓
Use transfer learning from a pre-trained model on ImageNet.
Why this is correct
Transfer learning leverages learned features, improving generalization.
- ✗
Increase the batch size to reduce variance.
Why it's wrong here
Larger batch sizes often lead to poorer generalization.
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Last reviewed: Jul 4, 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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