AWS Certified Machine Learning Engineer – Associate (MLA-C01) — Question 69

A company is running ML models on premises by using custom Python scripts and proprietary datasets. The company is using PyTorch. The model building requires unique domain knowledge. The company needs to move the models to AWS.
Which solution will meet these requirements with the LEAST effort?

Answer options

• A. Use SageMaker built-in algorithms to train the proprietary datasets.
• B. Use SageMaker script mode and premade images for ML frameworks.
• C. Build a container on AWS that includes custom packages and a choice of ML frameworks.
• D. Purchase similar production models through AWS Marketplace.

Correct answer: B

Explanation

Option B is correct because SageMaker script mode allows for easy integration of custom scripts while leveraging pre-made images, reducing the effort required for setup. Option A would involve reworking the datasets to fit built-in algorithms, which may require more effort. Option C demands creating and managing custom containers, which is more complex than using SageMaker's built-in capabilities. Option D does not address the need for custom model building, as it suggests purchasing rather than developing.