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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?
A
Text-based foundation model (NLP)
B
Image generation model
C
Embedding model
D
Code generation model
Explanation:
The correct answer is A) Text-based foundation model (NLP) because:
Natural Language Processing (NLP) models are specifically designed to understand, interpret, and analyze human language
Emotion detection in customer reviews involves understanding sentiment, tone, and emotional context from text data
Text-based foundation models can classify emotions like happiness, anger, and frustration from written text
Amazon Bedrock offers various NLP foundation models that are trained for sentiment analysis and emotion detection tasks
Other options are not suitable:
B) Image generation model: Used for creating images, not analyzing text
C) Embedding model: Converts text to numerical vectors but doesn't directly perform emotion classification
D) Code generation model: Designed for generating programming code, not analyzing customer sentiment
For emotion detection in customer reviews, a text-based NLP foundation model is the most appropriate choice as it can understand linguistic patterns and contextual cues that indicate different emotional states.