Natural Language Processing (NLP) is a subfield of artificial intelligence (AI) that focuses on the interaction between computers and humans through natural language. This guide provides an overview of NLP, its applications, and the fundamental concepts you need to understand to get started.
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, or adjective.
- Named Entity Recognition (NER): Identifying and categorizing entities in text, such as names of people, organizations, locations, and more.
- Sentiment Analysis: Determining the sentiment or emotional tone of 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 and intent behind queries.
- Chatbots: Creating conversational agents that can interact with users in a natural way.
- Machine Translation: Translating text from one language to another with high accuracy.
- Text Summarization: Automatically generating summaries of long texts.
Getting Started
To get started with NLP, you can explore the following resources:
- Natural Language Toolkit (NLTK) Documentation: A leading platform for building Python programs to work with human language data.
- spaCy Documentation: An industrial-strength NLP library for Python.
NLP Diagram
For more information on NLP and its applications, check out our Advanced NLP Techniques course.