AWS Certified Cloud Practitioner
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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?
Real Exam
Community
RRitesh
0
A
SageMaker Ground Truth
B
SageMaker Studio
C
SageMaker Autopilot
D
SageMaker Clarify
E
SageMaker Debugger
F
SageMaker Model Monitor
Explanation:
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:
- It can help automate the labeling process using ML models
- It can supplement their limited internal annotators with external human labelers
- It provides specialized workflows for medical imaging data
- 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
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