Natural Language Processing (NLP)

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Natural Language Processing is a sub-field of AI focused on enabling computers to understand and process human languages. It helps computers work with spoken and written language by extracting useful …

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NLP is needed because human language is rich, flexible, and often ambiguous, while computers need clear and structured input. NLP helps machines read, understand, and make sense of language in a usefu…

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Natural language is language that is spoken and written by people. NLP tries to extract information from this spoken and written language using algorithms.

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Unstructured data is data that does not fit neatly into the row-and-column format of relational databases. Conversation text, comments, declarations, and tweets are examples of unstructured data.

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The ultimate objective of NLP is to read, decipher, understand, and make sense of human languages in a valuable manner. The goal is for computers to achieve human-like comprehension of text and langua…

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NLP is difficult because computers traditionally need precise, unambiguous, structured language, while human speech is often ambiguous. Slang, regional dialects, social context, and unclear wording ma…

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The character 's' is an example of a low-level rule in natural language because it can signify plurality. This shows that even small details in language carry meaning.

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Text generation is a process where an AI system produces written content, imitating human language patterns and styles. It can create stories, poems, articles, summaries, and even code.