MLA-C01 Deployment and Orchestration of ML Workflows Practice Question
Which SageMaker feature compiles a trained model into an optimized binary for a specific hardware target (e.g., Intel, ARM, NVIDIA, or edge devices) to improve inference performance?
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 Neo
SageMaker Neo is a model compilation service that optimizes models for specific hardware targets. Amazon Elastic Inference attaches GPU acceleration to endpoints, but does not compile models. Model Monitor monitors quality. SageMaker Clarify explains predictions.
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 Model Monitor
Why it's wrong here
Model Monitor tracks model quality drift, not compilation.
- ✓
SageMaker Neo
Why this is correct
Neo compiles models to run efficiently on target hardware including edge devices.
- ✗
Amazon Elastic Inference
Why it's wrong here
Elastic Inference attaches GPU acceleration but does not compile the model.
- ✗
SageMaker Clarify
Why it's wrong here
Clarify helps with explainability and bias detection.
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