- Natural Language Toolkit Tutorial
- Natural Language Toolkit - Home
- Natural Language Toolkit - Introduction
- Natural Language Toolkit - Getting Started
- Natural Language Toolkit - Tokenizing Text
- Training Tokenizer & Filtering Stopwords
- Looking up words in Wordnet
- Stemming & Lemmatization
- Natural Language Toolkit - Word Replacement
- Synonym & Antonym Replacement
- Corpus Readers and Custom Corpora
- Basics of Part-of-Speech (POS) Tagging
- Natural Language Toolkit - Unigram Tagger
- Natural Language Toolkit - Combining Taggers
- Natural Language Toolkit - More NLTK Taggers
- Natural Language Toolkit - Parsing
- Chunking & Information Extraction
- Natural Language Toolkit - Transforming Chunks
- Natural Language Toolkit - Transforming Trees
- Natural Language Toolkit - Text Classification
- Natural Language Toolkit Resources
- Natural Language Toolkit - Quick Guide
- Natural Language Toolkit - Useful Resources
- Natural Language Toolkit - Discussion
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
Natural Language Toolkit Tutorial
Language is a method of communication with the help of which we can speak, read and write. Natural Language Processing (NLP) is the sub field of computer science especially Artificial Intelligence (AI) that is concerned about enabling computers to understand and process human language. We have various open-source NLP tools but NLTK (Natural Language Toolkit) scores very high when it comes to the ease of use and explanation of the concept. The learning curve of Python is very fast and NLTK is written in Python so NLTK is also having very good learning kit. NLTK has incorporated most of the tasks like tokenization, stemming, Lemmatization, Punctuation, Character Count, and Word count. It is very elegant and easy to work with.
Audience
This tutorial will be useful for graduates, post-graduates, and research students who either have an interest in NLP or have this subject as a part of their curriculum. The reader can be a beginner or an advanced learner.
Prerequisites
The reader must have basic knowledge about artificial intelligence. He/she should also be aware of basic terminologies used in English grammar and Python programming concepts.