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Python Text Processing with NLTK 2.0 Cookbook [Paperback]

Jacob Perkins
4.0 out of 5 stars  See all reviews (2 customer reviews)
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Book Description

12 Nov 2010 1849513600 978-1849513609
Use Python's NLTK suite of libraries to maximize your Natural Language Processing capabilities. * Quickly get to grips with Natural Language Processing ? with Text Analysis, Text Mining, and beyond * Learn how machines and crawlers interpret and process natural languages * Easily work with huge amounts of data and learn how to handle distributed processing * Part of Packt's Cookbook series: Each recipe is a carefully organized sequence of instructions to complete the task as efficiently as possible In Detail Natural Language Processing is used everywhere ? in search engines, spell checkers, mobile phones, computer games ? even your washing machine. Python's Natural Language Toolkit (NLTK) suite of libraries has rapidly emerged as one of the most efficient tools for Natural Language Processing. You want to employ nothing less than the best techniques in Natural Language Processing ? and this book is your answer. Python Text Processing with NLTK 2.0 Cookbook is your handy and illustrative guide, which will walk you through all the Natural Language Processing techniques in a step?by-step manner. It will demystify the advanced features of text analysis and text mining using the comprehensive NLTK suite. This book cuts short the preamble and you dive right into the science of text processing with a practical hands-on approach. Get started off with learning tokenization of text. Get an overview of WordNet and how to use it. Learn the basics as well as advanced features of Stemming and Lemmatization. Discover various ways to replace words with simpler and more common (read: more searched) variants. Create your own corpora and learn to create custom corpus readers for JSON files as well as for data stored in MongoDB. Use and manipulate POS taggers. Transform and normalize parsed chunks to produce a canonical form without changing their meaning. Dig into feature extraction and text classification. Learn how to easily handle huge amounts of data without any loss in efficiency or speed. This book will teach you all that and beyond, in a hands-on learn-by-doing manner. Make yourself an expert in using the NLTK for Natural Language Processing with this handy companion. What you will learn from this book * Learn Text categorization and Topic identification * Learn Stemming and Lemmatization and how to go beyond the usual spell checker * Replace negations with antonyms in your text * Learn to tokenize words into lists of sentences and words, and gain an insight into WordNet * Transform and manipulate chunks and trees * Learn advanced features of corpus readers and create your own custom corpora * Tag different parts of speech by creating, training, and using a part-of-speech tagger * Improve accuracy by combining multiple part-of-speech taggers * Learn how to do partial parsing to extract small chunks of text from a part-of-speech tagged sentence * Produce an alternative canonical form without changing the meaning by normalizing parsed chunks * Learn how search engines use Natural Language Processing to process text * Make your site more discoverable by learning how to automatically replace words with more searched equivalents * Parse dates, times, and HTML * Train and manipulate different types of classifiers Approach The learn-by-doing approach of this book will enable you to dive right into the heart of text processing from the very first page. Each recipe is carefully designed to fulfill your appetite for Natural Language Processing. Packed with numerous illustrative examples and code samples, it will make the task of using the NLTK for Natural Language Processing easy and straightforward. Who this book is written for This book is for Python programmers who want to quickly get to grips with using the NLTK for Natural Language Processing. Familiarity with basic text processing concepts is required. Programmers experienced in the NLTK will also find it useful. Students of linguistics will find it invaluable.

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Product details

  • Paperback: 272 pages
  • Publisher: Packt Publishing (12 Nov 2010)
  • Language: English
  • ISBN-10: 1849513600
  • ISBN-13: 978-1849513609
  • Product Dimensions: 1.4 x 23.1 x 18.8 cm
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (2 customer reviews)
  • Amazon Bestsellers Rank: 527,913 in Books (See Top 100 in Books)

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Overall the book is easy to read, has a huge set of sample recipes and feels very useful :- Ian Ozsvald --

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Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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1 of 1 people found the following review helpful
4.0 out of 5 stars Excellent cookbook for NLTK 30 Jan 2011
This is an excellent cookbook for Python's NLTK 2.0 module. Despite having used NLTK over the years I still found lots of useful recipes (and a whole pile of things I didn't know). Jacob also introduces external tools like Redis, MongoDB, execnet (for distributed computation) and dateutil (a wonderfully powerful datetime parser).

Disclosure - I was sent a copy of the book for review (unpaid, just a free copy as I've reviewed other Python books). This review represents my opinion and isn't influenced by Packt.

Early topics in the book include the cleaning and preparation of text, later classifiers are trained to solve specific problems and large scale computation (using Redis and execnet) is introduced.

There's a longer review broken down by chapters on my blog (google for 'ozsvald' and the book's title) if you want more detail. The blog review includes links to wikipedia and project sites for many of the topics covered in the book.
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4.0 out of 5 stars very useful, but 17 Nov 2013
Format:Paperback|Verified Purchase
I haven't yet used this book for serious development, but it covers systematically the NLTK facilities that I will use. I have hedged my bets by also buying the O'Reilly book on NLKT, but this looks a less useful and will be used as a secondary source. What is is missing for me is any comprehensive listing of all the facilities available within NLTK and I will have to look elsewhere for that.
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Most Helpful Customer Reviews on (beta) 4.0 out of 5 stars  7 reviews
8 of 8 people found the following review helpful
5.0 out of 5 stars Easier to implement than "Natural Language Processing with Python" 15 Mar 2012
By hellopenguin - Published on
I've been coding in perl for more than 10 years, and recently picked up python to do natural language processing. So I am new to both python and NLTK. I started off with the popular "Natural Language Processing with Python" by Bird, Klein, and Loper. I found it hard to follow because the dots were not connected. In that book, I'd read an example, and I *thought* I understood it, but coding it was a different story because there was no transition between the different sections. So I had to go to github to find random sample code using the tools I was interested in.

Then I picked up NLTK 2.0 Cookbook. It doesn't spend much time explaining concepts, but I find I can type the code in pretty much word-for-word (and replace it with my customized needs), and the code works. I find it much more useful, and faster to code using this book as a template. It's limited in the recipes it gives, but provides the main NLTK recipes, so I'm quite happy with it.

Since I had already picked up the Bird book, I knew exactly which recipes I needed. If you don't know which chapters are pertinent to your needs, I could see it being difficult to know which recipes to use because there's not much explanation and the terminology is different if you're new to natural language processing. The terminology and concepts are better explained in the Bird book.

A good book. Worth checking out some sample pages on Amazon to see if the recipes will be useful to you, and if you're finding difficulty implementing what's in the Bird book, this one provides better instructions.
1 of 1 people found the following review helpful
4.0 out of 5 stars Useful examples 25 Dec 2012
By Crabby Techie - Published on
Format:Kindle Edition|Verified Purchase
I've been working my way through the book as I build a pipeline for tagging & classifying text. The examples are straightforward and useful. It's a good collection of the most common tasks you'll need to do with NLTK.
1 of 1 people found the following review helpful
5.0 out of 5 stars Very practical book 6 Dec 2011
By Junling Hu - Published on
I found this book to be clear and very well written. All the examples are easy to follow, and the code are ready to use. It is a very practical book. I really want to thank the authors to put all the information together. It's an invaluable service.
5.0 out of 5 stars this book is a masterpiece on beginning nlp 4 May 2014
By John Wheeler - Published on
excellent book for nailing down the terminology, concepts, and getting a high-level understanding of the mechanics of NLP in any language.
4.0 out of 5 stars Good book on text processing 23 April 2013
By JoeT - Published on
Format:Paperback|Verified Purchase
First off, you better have some idea on how to run python. I use pearl and php regularly and had only a smattering of python knowledge, so the setup was not cookbook. Once I got past that, the code on the supplied CD worked as advertised. Good intro to text processing. However, if you want to understand what's really going on, you will need to understand python code in depth, in my opinion.
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