Natural Language Processing (NLP) is a field of artificial intelligence that focuses on the interaction between computers and humans through natural language. This documentation provides an overview of NLP concepts, tools, and resources available on our site.

Key Concepts

  • Tokenization: The process of breaking text down 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, adjective, etc.
  • Named Entity Recognition (NER): Identifying and categorizing entities in text, such as people, organizations, locations, and dates.
  • Sentiment Analysis: Determining the sentiment or opinion expressed in a piece of text, such as positive, negative, or neutral.

Resources

Tools

  • NLTK: The Natural Language Toolkit is a leading platform for building Python programs to work with human language data.
  • spaCy: An industrial-strength natural language processing library that provides various NLP features like tokenization, named entity recognition, and dependency parsing.

Images

Here are some images related to NLP:

Natural Language Processing
Tokenization
Named Entity Recognition
Sentiment Analysis

For more information on NLP, please visit our NLP Resources page.