Tutorials
Natural Language Processing with Python (NLTK Book)
- The definitive textbook by Bird, Klein & Loper on foundational NLP concepts: tokenization, tagging, parsing, classification, semantics, and more. Suitable as both a learning course and long-term reference.
Real Python – Natural Language Processing With Python’s NLTK Package
- A practical, beginner-friendly guide demonstrating how to use NLTK for tokenization, stop-word removal, stemming, part-of-speech tagging, named entity recognition, and frequency analysis in Python.
Real Python – Natural Language Processing With spaCy in Python
- A detailed tutorial on spaCy, covering its fast processing pipeline including tokenization, part-of-speech tagging, named entity recognition, and dependency parsing, suitable for production and research use.
TextBlob Quickstart Tutorial
- The official guide for TextBlob, showing how to perform sentiment analysis, noun phrase extraction, and part-of-speech tagging with a simple, beginner-friendly API.
Python Text Analysis Fundamentals (dlab‑Berkeley GitHub)
- An academic-grade Jupyter Notebook repository that covers tokenization, frequency counts, topic modeling, and sentiment analysis through well-documented examples.
Text Analysis in Python – PythonForBeginners.com
- A step-by-step tutorial introducing basic NLP techniques using Python’s standard libraries and TextBlob, focusing on tokenization and frequency distribution.
Python for NLP: Introduction to the Pattern Library – Stack Abuse
- An introduction to the Pattern library for NLP and web mining. Demonstrates installation, tokenization, POS tagging, lemmatization, sentiment analysis, and web data extraction in Python.
