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Exam AWS Certified Machine Learning Engineer - Associate MLA-C01 All Questions

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Exam AWS Certified Machine Learning Engineer - Associate MLA-C01 topic 1 question 62 discussion

An ML engineer has developed a binary classification model outside of Amazon SageMaker. The ML engineer needs to make the model accessible to a SageMaker Canvas user for additional tuning.
The model artifacts are stored in an Amazon S3 bucket. The ML engineer and the Canvas user are part of the same SageMaker domain.
Which combination of requirements must be met so that the ML engineer can share the model with the Canvas user? (Choose two.)

  • A. The ML engineer and the Canvas user must be in separate SageMaker domains.
  • B. The Canvas user must have permissions to access the S3 bucket where the model artifacts are stored.
  • C. The model must be registered in the SageMaker Model Registry.
  • D. The ML engineer must host the model on AWS Marketplace.
  • E. The ML engineer must deploy the model to a SageMaker endpoint.
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Suggested Answer: BC 🗳️

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Saransundar
1 month ago
Selected Answer: BC
For model outside of Amazon SageMaker, canvas user needs access to S3; Model --> Model registry
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GiorgioGss
1 month, 1 week ago
Selected Answer: BC
That's basic how Sagemaker works.
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