AIF-C01 Question 189
Single answerYou are a data scientist working for a healthcare startup that must comply with strict regulations requiring model transparency and explainability. You are tasked with documenting and sharing details about your machine learning model, including its purpose, training data, performance metrics, and limitations, to facilitate regulatory compliance. Which tool or approach should you use to achieve this in AWS?
- A
Amazon SageMaker Model Cards
- B
Amazon SageMaker Ground Truth
- C
Amazon Comprehend
- D
AWS Glue
Show answer and explanation
Correct answer: A
Explanation
Amazon SageMaker Model Cards are specifically designed to help teams document and share details about machine learning models in a standardized format. This tool supports regulatory compliance by promoting transparency and explainability, which makes it the most suitable choice in this scenario.
- A. Correct.
Amazon SageMaker Model Cards provide a standardized framework for documenting key details about machine learning models, such as their purpose, dataset, performance metrics, and limitations. This makes it the correct choice for ensuring transparency and explainability.
- B. Incorrect.
Amazon SageMaker Ground Truth is primarily used for creating and managing labeled datasets, not for documenting or sharing model details.
- C. Incorrect.
Amazon Comprehend is an NLP service for extracting insights from text, and it does not support documenting or explaining machine learning models.
- D. Incorrect.
AWS Glue is a data integration service used for preparing and transforming data, and it does not provide features for documenting models or ensuring transparency.