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Answer: Identifies potential bias during data preparation
Amazon SageMaker Clarify is specifically designed to help detect and measure potential bias in machine learning models and data. It provides tools to identify bias during data preparation, training, and after deployment. The other options describe different AWS services: - A: RAG workflows are typically handled by services like Amazon Bedrock or custom implementations - B: Model quality monitoring in production is handled by Amazon SageMaker Model Monitor - C: Documenting critical details about ML models is typically done through model cards or documentation practices, not specifically by SageMaker Clarify
Author: Ritesh Yadav
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Which functionality does Amazon SageMaker Clarify provide?
A
Integrates a Retrieval Augmented Generation (RAG) workflow
B
Monitors the quality of ML models in production
C
Documents critical details about ML models
D
Identifies potential bias during data preparation
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