MLA-C01 ML Model Development Practice Question

A company uses SageMaker Autopilot to build a binary classification model. The generated leaderboard shows an ensemble model as the best candidate. The team needs a model that can be deployed for real-time inference with latency < 10ms. What should they do?

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

✓

Select the best single model from the leaderboard (non-ensemble candidate) and deploy it

Autopilot ensemble models may have high latency due to combining multiple models. The team should evaluate non-ensemble candidates (single model) from the leaderboard to meet latency requirements.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✗
Use SageMaker Inference Recommender to profile the ensemble model and optimize it
Why it's wrong here
Inference Recommender helps with instance selection but won't reduce ensemble latency below a single model.
✗
Deploy the ensemble model as a SageMaker endpoint; ensemble models are optimized for low latency
Why it's wrong here
Ensemble models typically have higher latency; they may not meet <10ms.
✗
Retrain the ensemble model with fewer base estimators using a custom container
Why it's wrong here
This is complex and not directly supported; better to use a single model.
✓
Select the best single model from the leaderboard (non-ensemble candidate) and deploy it
Why this is correct
Single models usually have lower latency; evaluate if it meets the latency requirement.

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MLA-C01 ML Model Development Practice Question

Why each option matters

Option-by-option breakdown

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