Natural Language Processing (NLP) is a field of artificial intelligence that focuses on the interaction between computers and humans through natural language. This tutorial will cover the basics of NLP, including its history, key concepts, and applications.

Key Concepts

  • Tokenization: The process of breaking text into words, phrases, symbols, or other meaningful elements called tokens.
  • Part-of-Speech Tagging: Assigning a part of speech to each word in a sentence, such as noun, verb, or adjective.
  • Named Entity Recognition (NER): Identifying and classifying named entities in text, such as names, locations, and organizations.
  • Sentiment Analysis: Determining the sentiment or emotion behind a piece of text, such as positive, negative, or neutral.

Applications

NLP has a wide range of applications, including:

  • Search Engines: Improving search results by understanding the context of queries.
  • Chatbots: Creating conversational agents that can interact with users in natural language.
  • Machine Translation: Translating text from one language to another.
  • Voice Assistants: Enabling devices to understand and respond to spoken commands.

Natural Language Processing Diagram

For more information on NLP, check out our Advanced NLP Techniques tutorial.