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
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:
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Automatic labeling: Uses active learning and machine learning models to pre-label data
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Human labeling: Integrates with human workforce through Amazon Mechanical Turk or third-party vendors
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Workflow management: Creates labeling workflows and manages the labeling process
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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:
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It can help automate the labeling process using ML models
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It can supplement their limited internal annotators with external human labelers
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It provides specialized workflows for medical imaging data
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It ensures data privacy and security compliance for healthcare data
The other options serve different purposes:
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SageMaker Studio: Integrated development environment
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SageMaker Autopilot: Automated model building
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SageMaker Clarify: Model bias detection and explainability
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SageMaker Debugger: Model training monitoring and debugging
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SageMaker Model Monitor: Model performance monitoring in production
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