NLP

glosario nlp

1. What’s NLP?

NLP or “Natural Language Processing”, is a branch of artificial intelligence that deals with the interaction between computers and human language. Its main goal is to allow machines to understand, interpret and generate text in a similar way to how humans do. NLP involves a series of techniques and algorithms designed to analyze and understand the structure and meaning of natural language such as semantic analysis, word tokenization or semantic entity counting.

2. What’s the function of NLP?

Natural Language Processing (NLP) plays crucial roles in enabling machines to understand, interpret and generate text similarly to humans. Using advanced artificial intelligence algorithms and techniques, NLP analyzes large amounts of text to extract meaningful information, classify documents, and perform text processing tasks such as automatic summarization. It facilitates the identification and classification of specific entities in text, such as names of people, organizations or dates, and its ability to evaluate the polarity of language allows for sentiment analysis, which is useful for monitoring opinions on social networks or product reviews.

Additionally, NLP boosts machine translation, enabling efficient communication between languages. This branch of AI is essential for the development of chatbots and automated conversation systems that understand and respond to queries in natural language, such as from LLM models such as GPT-4, BLOOM, or BARD. It also excels at extracting information, identifying specific details in long texts. In turn, its ability to automatically generate text makes it a valuable tool for creating summaries, answers to questions or even original content based on previous content history, opening opportunities in areas of data analysis and automation of any type of tasks related to written language.

3. Use examples of NLP.

  • Virtual assistans.
  • Conversational tools.
  • Creation of text summary.
  • Voice synthesis.
  • Text classification.
  • Words tokenization.
  • Semantic analysis.

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