Natural Language Processing (NLP) is a fascinating field within Artificial Intelligence (AI) that focuses on the interaction between computers and humans through natural language. This page provides a collection of tutorials that delve into the intricacies of NLP.
Basic Concepts
- Tokenization: The process of splitting text into words, phrases, symbols, or other meaningful elements called tokens.
- Part-of-Speech Tagging: Identifying the parts of speech for each word in a sentence, such as noun, verb, adjective, etc.
- Named Entity Recognition (NER): The task of identifying entities in text, such as people, organizations, locations, and more.
Popular Libraries
- 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 easy-to-use APIs for various NLP tasks.
Tutorials
Introduction to NLP with NLTK
This tutorial will guide you through the basics of NLP using the NLTK library. We'll cover tokenization, part-of-speech tagging, and more.
Sentiment Analysis with spaCy
In this tutorial, we'll explore how to perform sentiment analysis using the spaCy library. Sentiment analysis is the process of determining whether a piece of text is positive, negative, or neutral.
NER with spaCy
Named Entity Recognition (NER) is a powerful tool for extracting information from text. This tutorial will walk you through using spaCy to perform NER tasks.
Conclusion
NLP is a rapidly evolving field with endless possibilities. By exploring these tutorials, you'll gain a solid foundation in NLP and be well on your way to creating your own NLP applications.
Resources
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