AWS Certified AI Practitioner Practice Exam 2025 – All-in-One Resource to Master Your Certification Success!

Amazon SageMaker Clarify is specifically designed to measure model performance and assess fairness in machine learning workflows. It provides insightful metrics that help identify bias in your model's predictions and can analyze feature importance, allowing developers to understand how different variables affect the model's decisions. This capability is essential for ensuring that machine learning models are fair and equitable across diverse demographic groups.

In contrast, the other options serve different purposes. Amazon S3 is primarily a cloud storage solution for storing and retrieving data but does not provide direct tools for model performance assessment. Amazon DynamoDB is a NoSQL database service designed for low-latency data access, but it lacks functionalities for evaluating machine learning models. Finally, Amazon QuickSight is a business analytics service for visualizing data and creating dashboards, which can analyze datasets but doesn't directly focus on measuring model performance or fairness in the context of machine learning. Therefore, Amazon SageMaker Clarify stands out as the most relevant tool for these tasks.