AWS Certified Cloud Practitioner
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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?
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RRitesh
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.
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