MLA-C01 ML Model Development Practice Question
A machine learning engineer is preparing a training job on SageMaker with a custom Docker container. Which TWO actions are required to use the container with SageMaker? (Choose TWO.)
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
✓
Push the container image to Amazon ECR
To use a custom container, you must push it to Amazon ECR and specify the registry path in the estimator. The container must also implement the SageMaker training contract (like /opt/ml), but that is part of building the image.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Push the container image to Amazon ECR
Why this is correct
ECR is the registry for Docker images used by SageMaker.
- ✓
Use a SageMaker Estimator with image_uri parameter pointing to the ECR image
Why this is correct
The Estimator must reference the ECR image URI.
- ✗
Upload the container image to Amazon S3
Why it's wrong here
Container images are stored in ECR, not S3.
- ✗
Enable SageMaker Debugger to monitor the custom container
Why it's wrong here
Debugger is optional, not required.
- ✗
Register the container in SageMaker Model Registry
Why it's wrong here
Model Registry is for models, not training containers.
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