Python 3 Text Processing with NLTK 3 Cookbook Illustrated Edition

by Jacob Perkins (Author)

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ISBN-13: 978-1782167853

ISBN-10: 1782167854

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Over 80 practical recipes on natural language processing techniques using Python's NLTK 3.0

About This Book

Break text down into its component parts for spelling correction, feature extraction, and phrase transformation
Learn how to do custom sentiment analysis and named entity recognition
Work through the natural language processing concepts with simple and easy-to-follow programming recipes

Who This Book Is For

This 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 built-in 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

In Detail

This book will show you the essential techniques of text and language processing. Starting with tokenization, stemming, and the WordNet dictionary, you'll progress to part-of-speech tagging, phrase chunking, and named entity recognition. You'll learn how various text corpora are organized, as well as how to create your own custom corpus. Then, you'll move onto text classification with a focus on sentiment analysis. And because NLP can be computationally expensive on large bodies of text, you'll try a few methods for distributed text processing. Finally, you'll be introduced to a number of other small but complementary Python libraries for text analysis, cleaning, and parsing.

This cookbook provides simple, straightforward examples so you can quickly learn text processing with Python and NLTK.

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Editorial Reviews

About the Author

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.

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Product details

Publisher ‏ : ‎ Packt Publishing; Illustrated edition (August 26, 2014)
Language ‏ : ‎ English
Paperback ‏ : ‎ 304 pages
ISBN-10 ‏ : ‎ 1782167854
ISBN-13 ‏ : ‎ 978-1782167853
Item Weight ‏ : ‎ 1.16 pounds
Dimensions ‏ : ‎ 7.5 x 0.69 x 9.25 inches

Best Sellers Rank: #2,312,095 in Books (See Top 100 in Books)
- #387 in Natural Language Processing (Books)
- #2,104 in Data Processing
- #2,521 in Python Programming

Customer Reviews:
17 ratings

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Jacob Perkins

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Jacob Perkins is an open source programmer, NLP hacker, and startup entrepreneur. He is currently the CTO & co-founder of Weotta, a semantic search engine for local events, activities, restaurants and more. His major open source contributions are to NLTK, a Python toolkit for natural language processing, and Seahorse, the Gnome encryption key application.

Customer reviews

5 star		36%
4 star		17%
3 star		17%
2 star		16%
1 star		14%

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Alfredo Menendez

It's ok as an introduction, for example, when ...

Reviewed in the United States on February 4, 2017

Verified Purchase

It's ok as an introduction, for example, when you are totally new to NLTK. However I found solutions are not the most effective nor very thorough.

Helpful

Luis Felipe Yepez Barrios

Good Book

Reviewed in the United States on February 15, 2019

Good book

Reviewed in the United States on February 8, 2017

Verified Purchase

Informative

Helpful

Roy

Why did I pay for this?

Reviewed in the United States on January 17, 2019

Verified Purchase

Short on information. Would not buy this textbook again.

Helpful

Sheng-miao Kung

Five Stars

Reviewed in the United States on November 19, 2017

Verified Purchase

It's a GREAT book!

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Scott Steele

Maybe worth half the price (currenly $16.54)

Reviewed in the United States on December 4, 2014

Verified Purchase

I'm rating this book relative to "Natural Language Processing with Python" (2009) - which you can currently get for free at http://www.nltk.org/book_1ed/. Unfortunately, the 2ed of that book won't be available until 2016.

This book pales in comparison in communication, content, and utility as it relates to both NLTK and Python (in general) - you don't even get a table of contents.

8 people found this helpful

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fazel Keshtkar

Waste of money

Reviewed in the United States on August 18, 2015

Verified Purchase

Very poor book-
A lot of content provided without proper resources.
Many of his red URL or package are out dated and not useful at all.
Very irresponsible author- i contact author about many issues he never ever answered

4 people found this helpful

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E. Martin

It is a cookbook of recipes for how to build effective text mining applications quickly and without wasted time in python and it

Reviewed in the United States on December 3, 2015

This is not a book on the origins of text mining or the theory. It is a cookbook of recipes for how to build effective text mining applications quickly and without wasted time in python and it is awesome at doing that. There are some tools it does not cover and it does not hit areas like predictive analytics or predictive text mining, but as a get started book, I don't know of any other better resource. The alternative seems to be trying to piece all this together on the web and that is just ineffective.

So, if you want to know how to adopt NLTK, Wordnet, Scipy, Numpy, and the like to the problems you are facing right now this is your book. It will have you up and running in hours, not weeks, with plenty of code recipes included. The author also maintains an excellent blog, streamhacker.com, if you want to get a sense for his knowledge and writing style before buying. It's how I found this book.

An excellent next book, if you need a more complete book to build your own fundamental tools, rather than simply adopting NLTK, is Fundamentals of Predictive Text Mining by Weiss. Fundamentals will take you from the launch point provided by this book into computational and predictive methods.

9 people found this helpful

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Top reviews from other countries

rakesh patra

Must have for any NLP researcher

Reviewed in India on August 27, 2021

Verified Purchase

It’s a very good information and with lots of hands on code. Really useful for ppl who are in there mid journey on NLP research

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Python 3 Text Processing with NLTK 3 Cookbook Illustrated Edition

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