Exam MLA-C01 Topic 2 Question 83 Discussion

Actual exam question for Amazon's MLA-C01 exam
Question #: 83
Topic #: 2
A company uses a training job on Amazon SageMaker Al to train a neural network. The job first trains a model and then evaluates the model's performance ag test dataset. The company uses the results from the evaluation phase to decide if the trained model will go to production.
The training phase takes too long. The company needs solutions that can shorten training time without decreasing the model's final performance.
Select the correct solutions from the following list to meet the requirements for each description. Select each solution one time or not at all. (Select THREE.)
. Change the epoch count.
. Choose an Amazon EC2 Spot Fleet.
Change the batch size.
. Use early stopping on the training job.
Use the SageMaker Al distributed data parallelism (SMDDP) library.
. Stop the training job.

Suggested Answer:


Explanation:
Change the number of samples used in each iteration of training
Correct selection:
Change the batch size
Why:
Increasing the batch size reduces the number of iterations per epoch, which can significantly shorten training time while maintaining model quality when tuned appropriately. AWS explicitly recommends batch size tuning as a primary performance optimization.
Increase the number of instances used during training
Correct selection:
Use the SageMaker AI distributed data parallelism (SMDDP) library
Why:
SMDDP is designed to efficiently distribute training data across multiple GPU instances with optimized gradient synchronization. This accelerates training without affecting model convergence or accuracy, unlike naive scaling approaches.
Stop training before the maximum number of epochs are reached if performance is sufficient and not improving Correct selection:
Use early stopping on the training job
Why:
Early stopping automatically terminates training when validation metrics stop improving. AWS recommends this to reduce wasted compute time while preserving optimal model performance.

by Beck at Apr 05, 2026, 03:07 AM

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