AWS Certified Cloud Practitioner
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A retail analytics company wants to analyze customer reviews and detect emotions such as happiness, anger, and frustration. Which foundation model type in Bedrock is most appropriate?
Real Exam
Community
RRitesh
A
Text-based foundation model (NLP)
B
Image generation model
C
Embedding model
D
Code generation model
Explanation:
Explanation:
Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies. For analyzing customer reviews and detecting emotions (happiness, anger, frustration), the most appropriate foundation model type is a Text-based foundation model (NLP).
Here's why:
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Natural Language Processing (NLP): Text-based foundation models are specifically designed for natural language understanding tasks, including sentiment analysis and emotion detection.
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Task Alignment: Emotion detection in text requires understanding context, semantics, and linguistic patterns - exactly what NLP models are trained to do.
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Other options are unsuitable:
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Image generation models: Used for creating images, not analyzing text
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Embedding models: Convert text to numerical vectors for similarity search, not direct emotion detection
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Code generation models: Designed for generating programming code, not analyzing natural language text
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Bedrock NLP Models: Amazon Bedrock offers various text-based foundation models like Anthropic's Claude, Amazon Titan, and others that can perform sentiment analysis and emotion detection tasks.
Correct Answer: A (Text-based foundation model (NLP))
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