AIF-C01 Question 190
Single answerA data science team has developed a machine learning model and wants to ensure the model is transparent and explainable for both internal stakeholders and external regulators. They also want to document the model's intended use, potential biases, and performance metrics. Which AWS service or tool should they use to achieve this goal?
- A
Amazon SageMaker Model Cards
- B
Amazon SageMaker Data Wrangler
- C
Amazon Lex
- D
Amazon Rekognition
Show answer and explanation
Correct answer: A
Explanation
Amazon SageMaker Model Cards is the appropriate tool for documenting machine learning models to ensure transparency, explainability, and compliance with internal or external requirements. It allows teams to record details such as intended use, performance metrics, and potential biases, making it ideal for this scenario.
- A. Correct.
Amazon SageMaker Model Cards is designed to document key details about machine learning models, including their intended use, performance metrics, and potential biases, making it suitable for transparency and explainability.
- B. Incorrect.
Amazon SageMaker Data Wrangler focuses on data preparation and transformation workflows, not on documenting model details or promoting transparency.
- C. Incorrect.
Amazon Lex is a service for building conversational interfaces such as chatbots and does not provide tools for documenting or explaining machine learning models.
- D. Incorrect.
Amazon Rekognition is used for image and video analysis and does not offer features for documenting or explaining machine learning models.