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Answer: SageMaker Ground Truth
**Explanation:** Amazon SageMaker Ground Truth is specifically designed for data labeling tasks. It provides: - **Automatic labeling**: Uses active learning and machine learning models to pre-label data - **Human labeling**: Integrates with human workforce through Amazon Mechanical Turk or third-party vendors - **Workflow management**: Creates labeling workflows and manages the labeling process - **Quality control**: Includes built-in quality controls and verification mechanisms For the healthcare startup working with X-ray images, SageMaker Ground Truth would be the ideal service because: 1. It can help automate the labeling process using ML models 2. It can supplement their limited internal annotators with external human labelers 3. It provides specialized workflows for medical imaging data 4. It ensures data privacy and security compliance for healthcare data The other options serve different purposes: - **SageMaker Studio**: Integrated development environment - **SageMaker Autopilot**: Automated model building - **SageMaker Clarify**: Model bias detection and explainability - **SageMaker Debugger**: Model training monitoring and debugging - **SageMaker Model Monitor**: Model performance monitoring in production
Author: Ritesh Yadav
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A healthcare startup is building a machine learning model to detect diseases from X-ray images. They need labeled data but have limited internal annotators. Which SageMaker service can assist with automatic and human labeling?
A
SageMaker Ground Truth
B
SageMaker Studio
C
SageMaker Autopilot
D
SageMaker Clarify
E
SageMaker Debugger
F
SageMaker Model Monitor