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A company wants an integrated development environment (IDE) to deploy a machine learning (ML) model. Which AWS service will meet this requirement?
A
AWS CodeBuild
B
Amazon CodeGuru
C
Amazon Athena
D
Amazon SageMaker Studio
Explanation:
Amazon SageMaker Studio is the correct choice because it provides a fully integrated development environment (IDE) specifically designed for machine learning workflows.
Key features of Amazon SageMaker Studio:
Complete ML development environment with Jupyter notebooks
Built-in tools for data preparation, model training, and deployment
Integrated debugging and profiling capabilities
One-click model deployment to production
Collaborative features for team-based ML development
Why other options are incorrect:
AWS CodeBuild: A continuous integration service for building and testing code, not specifically designed for ML model deployment
Amazon CodeGuru: A developer tool for code quality and performance recommendations, not an ML IDE
Amazon Athena: An interactive query service for analyzing data in Amazon S3 using SQL, not an ML development environment
Amazon SageMaker Studio provides the complete IDE experience needed for end-to-end ML model development and deployment.