Q: 4
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?
Options
Discussion
Option C SageMaker Model Registry with model groups is what it's built for. Pretty sure this is the lowest overhead way, fits the use case exactly.
Its C, official AWS exam guide and whitepapers cover model registry and groups directly.
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