AWS Certified AI Practitioner AIF-C01 Practice Question
A retailer wants to build a model that detects positive or negative sentiment from sentences written by customers in online product reviews. According to common AI data categories, how should this source information be classified?
Sentences written by customers are composed of words and characters, making the information unstructured textual content. Therefore, it is classified as text data. Image data contains pixels, tabular data is organized in rows and columns (for example, spreadsheets), and time-series data is sequential numerical or categorical measurements indexed by time-all of which are inappropriate descriptions for free-form written reviews.
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What makes text data 'unstructured' compared to other types of data?
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How does natural language processing (NLP) help analyze text data?
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What would be an example of a dataset that qualifies as tabular data?
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What is text data in AI?
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What is sentiment analysis and how does it work?
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How do natural language processing models handle text data?
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AWS Certified AI Practitioner AIF-C01
Fundamentals of AI and ML
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