AWS Certified AI Practitioner AIF-C01 Practice Question
A company builds several machine learning models in Amazon SageMaker and needs to capture each model's training data sources, evaluation metrics, and responsible owners in a standardized, discoverable report. Which SageMaker capability should they use to document this information?
SageMaker Model Cards provide a built-in mechanism to create a standardized report that documents a model's purpose, training data lineage, evaluation results, ownership, and other governance details. This satisfies the requirement for a single, discoverable place to record model provenance and accountability information. SageMaker Experiments offers lineage tracking for trials but does not generate a formal report for stakeholders. The AWS Glue Data Catalog inventories data sets, not models. Amazon Macie is for sensitive-data discovery and does not document model details.
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What are SageMaker Model Cards used for?
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How is SageMaker Experiments different from SageMaker Model Cards?
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Why can’t AWS Glue Data Catalog or Amazon Macie be used instead of SageMaker Model Cards?
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What are Amazon SageMaker Model Cards, and how do they help with model documentation?
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How are SageMaker Experiments different from SageMaker Model Cards?
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What are some examples of governance details captured in SageMaker Model Cards?
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AWS Certified AI Practitioner AIF-C01
Security, Compliance, and Governance for AI Solutions
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