Python 3 Text Processing with NLTK 3 Cookbook
Python 3 Text Processing with NLTK 3 Cookbook
2nd Edition
Published on 7. October 2025
304 pages
978-1-78216-786-0 (ISBN)
Description
Key Features
Book DescriptionThis book is intended for Python programmers interested in learning how to do natural language processing. Maybe you've learned the limits of regular expressions the hard way, or you've realized that human language cannot be deterministically parsed like a computer language. Perhaps you have more text than you know what to do with, and need automated ways to analyze and structure that text. This Cookbook will show you how to train and use statistical language models to process text in ways that are practically impossible with standard programming tools. A basic knowledge of Python and the basic text processing concepts is expected. Some experience with regular expressions will also be helpful.What you will learn
Tokenize text into sentences, and sentences into words
Look up words in the WordNet dictionary
Apply spelling correction and word replacement
Access the builtin text corpora and create your own custom corpus
Tag words with parts of speech
Chunk phrases and recognize named entities
Grammatically transform phrases and chunks
Classify text and perform sentiment analysis
Who this book is for
Book DescriptionThis book is intended for Python programmers interested in learning how to do natural language processing. Maybe you've learned the limits of regular expressions the hard way, or you've realized that human language cannot be deterministically parsed like a computer language. Perhaps you have more text than you know what to do with, and need automated ways to analyze and structure that text. This Cookbook will show you how to train and use statistical language models to process text in ways that are practically impossible with standard programming tools. A basic knowledge of Python and the basic text processing concepts is expected. Some experience with regular expressions will also be helpful.What you will learn
Tokenize text into sentences, and sentences into words
Look up words in the WordNet dictionary
Apply spelling correction and word replacement
Access the builtin text corpora and create your own custom corpus
Tag words with parts of speech
Chunk phrases and recognize named entities
Grammatically transform phrases and chunks
Classify text and perform sentiment analysis
Who this book is for
All prices
More details
Edition
2nd Revised edition
Language
English
Place of publication
Birmingham
United Kingdom
Target group
Professional and scholarly
US School Grade: College Graduate Student
Edition type
Revised edition
File size
1,66 MB
ISBN-13
978-1-78216-786-0 (9781782167860)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Jacob Perkins
Python 3 Text Processing with NLTK 3 Cookbook
Python 3 Text Processing with NLTK 3 Cookbook
Book
08/2014
2nd Edition
Packt Publishing
€56.10
Shipment within 3-4 weeks
Person
Perkins Jacob :
Jacob Perkins is the cofounder and CTO of Weotta, a local search company. Weotta uses NLP and machine learning to create powerful and easy-to-use natural language search for what to do and where to go. He is the author of Python Text Processing with NLTK 2.0 Cookbook, Packt Publishing, and has contributed a chapter to the Bad Data Handbook, O'Reilly Media. He writes about NLTK, Python, and other technology topics at http://streamhacker.com. To demonstrate the capabilities of NLTK and natural language processing, he developed http://text-processing.com, which provides simple demos and NLP APIs for commercial use. He has contributed to various open source projects, including NLTK, and created NLTK-Trainer to simplify the process of training NLTK models. For more information, visit https://github.com/japerk/nltk-trainer.
Jacob Perkins is the cofounder and CTO of Weotta, a local search company. Weotta uses NLP and machine learning to create powerful and easy-to-use natural language search for what to do and where to go. He is the author of Python Text Processing with NLTK 2.0 Cookbook, Packt Publishing, and has contributed a chapter to the Bad Data Handbook, O'Reilly Media. He writes about NLTK, Python, and other technology topics at http://streamhacker.com. To demonstrate the capabilities of NLTK and natural language processing, he developed http://text-processing.com, which provides simple demos and NLP APIs for commercial use. He has contributed to various open source projects, including NLTK, and created NLTK-Trainer to simplify the process of training NLTK models. For more information, visit https://github.com/japerk/nltk-trainer.
Content
Table of Contents
Tokenizing Text and WordNet Basics
Replacing and Correcting Words
Creating Custom Corpora
Tagging Part of Speech
Extraction Chunks: Partial Parsing
Transforming and Normalizing Chunks
Extracting Features for Classifying Words and Chunks
Distributed Processing and Handling Large Datasets
Parsing and Matching Specific Data
Appendix 1
Tokenizing Text and WordNet Basics
Replacing and Correcting Words
Creating Custom Corpora
Tagging Part of Speech
Extraction Chunks: Partial Parsing
Transforming and Normalizing Chunks
Extracting Features for Classifying Words and Chunks
Distributed Processing and Handling Large Datasets
Parsing and Matching Specific Data
Appendix 1
