AWS Certified AI Practitioner

Explanation:

SageMaker JumpStart is the correct answer because it provides pre-trained models, solution templates, and example notebooks that can be quickly deployed for various tasks including NLP sentiment analysis.

• SageMaker JumpStart: Offers pre-trained models, notebooks, and solution templates that can be deployed with just a few clicks, making it ideal for quickly deploying pre-trained models without building from scratch.
• SageMaker Ground Truth: Used for data labeling and annotation, not for deploying pre-trained models.
• SageMaker Feature Store: Used for storing, sharing, and managing ML features, not for deploying pre-trained models.
• SageMaker Canvas: A no-code tool for building ML models, but doesn't specifically focus on providing pre-trained models and notebooks like JumpStart does.

SageMaker JumpStart is specifically designed to help users quickly get started with ML by providing access to hundreds of pre-trained models across various domains, including NLP models for sentiment analysis, along with accompanying notebooks and deployment scripts.