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A team needs a unified web-based interface to build, train, debug, and deploy machine learning models in one place. Which SageMaker service provides this?
A
SageMaker Model Monitor
B
SageMaker Studio
C
SageMaker Neo
D
SageMaker Training Jobs
Explanation:
SageMaker Studio is the correct answer because it provides a unified web-based integrated development environment (IDE) for machine learning workflows.
Unified Interface: A single web-based interface that brings together all the tools needed for ML development
Complete ML Workflow Support:
Build: Jupyter notebooks, data preparation tools
Train: Model training with built-in algorithms and custom code
Debug: Debugging tools for ML models
Deploy: Model deployment and management
Collaboration: Team collaboration features
Integration: Seamless integration with other AWS services
A. SageMaker Model Monitor: This service is for monitoring deployed models for data drift and quality issues, not for building/training models.
C. SageMaker Neo: This is a compiler that optimizes models for different hardware platforms, not a development interface.
D. SageMaker Training Jobs: This is a service for running model training jobs, but it's not a unified web interface for the entire ML workflow.
SageMaker Studio is specifically designed to be the single pane of glass for data scientists and ML engineers to work on all aspects of machine learning projects.