ExamTopics Logo
Mail Us[email protected]
Menu
Amazon Discussions
exam questions

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

View all questions & answers for the AWS Certified Machine Learning Engineer - Associate MLA-C01 exam
Go to Exam

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

Exam question from Amazon's AWS Certified Machine Learning Engineer - Associate MLA-C01
Question #: 1
Topic #: 1
[All AWS Certified Machine Learning Engineer - Associate MLA-C01 Questions]

Case Study -
A company is building a web-based AI application by using Amazon SageMaker. The application will provide the following capabilities and features: ML experimentation, training, a central model registry, model deployment, and model monitoring.
The application must ensure secure and isolated use of training data during the ML lifecycle. The training data is stored in Amazon S3.
The company needs to use the central model registry to manage different versions of models in the application.
Which action will meet this requirement with the LEAST operational overhead?

  • A. Create a separate Amazon Elastic Container Registry (Amazon ECR) repository for each model.
  • B. Use Amazon Elastic Container Registry (Amazon ECR) and unique tags for each model version.
  • C. Use the SageMaker Model Registry and model groups to catalog the models.
  • D. Use the SageMaker Model Registry and unique tags for each model version.
Show Suggested Answer Hide Answer
Suggested Answer: C 🗳️
by Neo_2022 at Nov. 27, 2024, 5:12 a.m.
Disclaimers:
  • - ExamTopics website is not related to, affiliated with, endorsed or authorized by Amazon.
  • - Trademarks, certification & product names are used for reference only and belong to Amazon.

Comments

Chosen Answer:
This is a voting comment (?). It is better to Upvote an existing comment if you don't have anything to add.
Switch to a voting comment New
Submit Cancel
motk123
2 days, 19 hours ago
Selected Answer: C
C: The SageMaker Model Registry organizes models into Model Package Groups, tracks versions as Model Packages, and optionally aggregates groups into Collections. This structure ensures robust versioning and manageability for trained models. https://docs.aws.amazon.com/sagemaker/latest/dg/model-registry-models.html
upvoted 1 times
...
GiorgioGss
2 weeks, 1 day ago
Selected Answer: C
https://docs.aws.amazon.com/sagemaker/latest/dg/model-registry-models.html "Each model package in a Model Group corresponds to a trained model. The version of each model package is a numerical value that starts at 1 and is incremented with each new model package added to a Model Group. For example, if 5 model packages are added to a Model Group, the model package versions will be 1, 2, 3, 4, and 5."
upvoted 4 times
...
Neo_2022
2 weeks, 1 day ago
Selected Answer: C
https://aws.amazon.com/blogs/machine-learning/centralize-model-governance-with-sagemaker-model-registry-resource-access-manager-sharing/
upvoted 3 times
...
Community vote distribution
A (35%)
C (25%)
B (20%)
Other
Most Voted
A voting comment increases the vote count for the chosen answer by one.

Upvoting a comment with a selected answer will also increase the vote count towards that answer by one. So if you see a comment that you already agree with, you can upvote it instead of posting a new comment.

SaveCancel
exam
Someone Bought Contributor Access for:
SY0-701
London, 1 minute ago