MLS-C01 Practice Question: Machine Learning Implementation and Operations
A machine learning engineer is deploying a model to an Amazon SageMaker endpoint. The model requires GPU for inference. Which instance type should be selected?
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
✓
ml.p3.2xlarge
Ml.p3.2xlarge is a GPU-enabled instance (part of the P3 family) suitable for inference requiring GPU acceleration. Options B, C, and D (ml.m5.large, ml.c5.xlarge, ml.r5.large) are CPU-only instances and do not provide GPU capabilities.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
ml.p3.2xlarge
Why this is correct
GPU instance suitable for inference.
- ✗
ml.m5.large
Why it's wrong here
General purpose CPU instance.
- ✗
ml.c5.xlarge
Why it's wrong here
Compute optimized CPU instance.
- ✗
ml.r5.large
Why it's wrong here
Memory optimized CPU instance.
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