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Python 3 Text Processing With NLTK 3 Cookbook 2nd ed. Edition

by Jacob Perkins (Author)
3.5 out of 5 stars 20 ratings
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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

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.

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
Read more
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  1. ISBN-10
    1782167854
  2. ISBN-13
    978-1782167853
  3. Edition
    2nd ed.
  4. Publisher
    Packt Pub Ltd
  5. Publication date
    August 31, 2014
  6. Language
    English
  7. Dimensions
    7.5 x 0.75 x 9 inches
  8. Print length
    288 pages
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From the brand

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.

Product details

  • Publisher ‏ : ‎ Packt Pub Ltd; 2nd ed. edition (August 31, 2014)
  • Language ‏ : ‎ English
  • Paperback ‏ : ‎ 288 pages
  • ISBN-10 ‏ : ‎ 1782167854
  • ISBN-13 ‏ : ‎ 978-1782167853
  • Item Weight ‏ : ‎ 1.15 pounds
  • Dimensions ‏ : ‎ 7.5 x 0.75 x 9 inches
  • Customer Reviews:
    3.5 out of 5 stars 20 ratings

About the author

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Jacob Perkins

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.

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Top reviews from the United States

  • Luis Felipe Yepez Barrios
    5.0 out of 5 stars Good Book
    Reviewed in the United States on February 15, 2019
    Verified Purchase
    Good book
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  • Daniel Lee
    4.0 out of 5 stars Well explained, practical examples with solid theoretical groundings
    Reviewed in the United States on October 23, 2014
    In its introduction, the Python 3 Text Processing with NLTK 3 Cookbook claims to skip the preamble and ignore pedagogy, letting you jump straight into text processing. Although it does skip the preamble, I would argue that this statement is false - it definitely does not skip the pedagogy. The examples this book shows you are practical, understandable and well-explained.

    The book is intended for those familiar with Python who want to use it in order to process natural language. Following this credo, there is no discussion about software design and no attempt to make especially elegant code. I tend to nitpick at code quality, and although there was nothing that upset me in the code examples here, they didn't awe me with their subtle beauty. However, the raw power of NLTK, combined with the flexibility of Python, impressed me deeply.

    The author takes you on a trip through a large section of natural language processing, starting with text tokenization and using Wordnet. I really enjoyed ideas on computing the semantic "distance" between different words by traversing subset trees. It then continues on to show you how to replace and correct words, tag parts of speech intexts, chunk texts and transform text chunks, and how to classify text. The whole thing is rounded off by a discussion on distributed processing with some nice examples of how to use execnet as a simple but effective message passing interface.

    Reading all these examples made me want to go out and write a search engine or a text classifier - with NLTK, daunting tasks in this field become easy.

    Above and beyond the practical text processing material in this book, what I enjoyed most was its coverage of various machine learning algorithms. The book definitely is not about machine learning, but it affords you a glimpse into the world of machine learning in a way that you can understand what you're doing if you're just using what different libraries give you out of the box. I appreciated these more extended explanations, which I often miss in texts involving machine learning.
    9 people found this helpful
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  • Scott Steele
    2.0 out of 5 stars 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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  • Alfredo Menendez
    3.0 out of 5 stars 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.
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  • Sheng-miao Kung
    5.0 out of 5 stars Five Stars
    Reviewed in the United States on November 19, 2017
    Verified Purchase
    It's a GREAT book!
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  • kamazon
    1.0 out of 5 stars 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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  • dfc37
    4.0 out of 5 stars Most Packt content sucks and they are overall a shady publisher but I ...
    Reviewed in the United States on April 18, 2018
    Most Packt content sucks and they are overall a shady publisher but I can verify that I was actually able to use the high information words recipe to improve classification accuracy pretty substantially, so I definitely got concrete benefit with this one.
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  • Glenn W.
    5.0 out of 5 stars Five Stars
    Reviewed in the United States on February 8, 2017
    Verified Purchase
    Informative
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Top reviews from other countries

  • rakesh patra
    5.0 out of 5 stars 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
    Report