Which term describes the numerical representations of real-world objects and concepts that AI and natural language processing (NLP) models use to improve understanding of textual information?
A. Embeddings: Embeddings are numerical representations of words, phrases, or even entire documents. These representations capture the semantic meaning of the real-world objects and concepts and are used by AI and NLP models to improve their understanding of textual information. They help the model interpret and process language in a more meaningful way.
A. Embeddings
Explanation:
Embeddings are numerical representations of real-world objects, words, phrases, or concepts in a continuous vector space. They enable AI and Natural Language Processing (NLP) models to understand and process textual information by capturing the semantic relationships and contextual meanings of words and phrases.
Explanation:
Embeddings are numerical representations of real-world objects, concepts, or textual data. In AI and NLP, embeddings map words, phrases, or even entire documents to a high-dimensional vector space. This allows models to capture semantic relationships and improve understanding of the textual information
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