MLA-C01 Practice Test 1

A data science team runs a pandas and scikit-learn feature engineering script by hand inside an Amazon SageMaker Studio notebook. The raw dataset in Amazon S3 has grown to roughly 200 GB and the notebook now runs out of memory. The team wants the script to run on managed compute that is provisioned on demand and released when the script finishes, reads and writes S3, and can later be reused as a step in an automated ML workflow, with as few changes to the script as possible.

Which approach meets these requirements?