Lock-chamber fill time is a modest tabular regression with no custom loss. One engineer wants a blank PyTorch script, another wants a JumpStart foundation-model template, and a third wants a built-in estimator. Which path fits?
Select an answer to reveal the explanation.
Short Explanation
Think of modest tabular regression with no custom loss. Use a SageMaker built-in. Save script mode for custom training code and JumpStart for a pretrained template that already fits. A blank PyTorch script is the wrong rung.
Full Explanation
Climb the official ladder: a SageMaker built-in algorithm for a standard problem, JumpStart when a pretrained template already fits, and script mode only when a supported framework must carry custom training code. A blank PyTorch script and a foundation-model template are the wrong rung here. Polly is not that choice.