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Natural Language Processing with Python

4.12  ·  Rating details ·  369 Ratings  ·  33 Reviews
This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets us ...more
Paperback, 504 pages
Published July 7th 2009 by O'Reilly Media (first published January 1st 2009)
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Dec 08, 2011 rated it really liked it
Recommends it for: People who want to write software that analyses text
[Editor's preface to the second edition: notgettingenough read the first edition of this review and complained that it was all Geek to her. I have amended it accordingly]
POLONIUS: What do you read, my lord?
HAMLET: Words, words, words.
Hamlet was evidently interested in textual analysis, and if the Python Natural Language Toolkit (NLTK) had been available in Elsinore I'm sure he'd have bought this book too. I'd heard good things about it, and it doesn't disappoint: the authors have done a terrific
Aug 27, 2014 rated it really liked it
Shelves: technical
I'm sure I'll come back to this book again, and again. It's a truly good one - not only I got to start learning the basics of text mining in Python using nltk, but also I learned some basics of Python data processing ideas and routines. It's a shame that with my limited knowledge so far, I can only devour very little value out of reading it. Definitely a five star!
Excellent intro to both Python programming and NLP. Assumes no prior familiarity with either, so this is a good book both for beginning CS students who know little to nothing about linguistics, and for beginning linguists who have no programming experience.
Rob Young
Aug 15, 2010 rated it really liked it
This is a fascinating book. Everything from text processing to statistics to lexical analysis. For most problems the solution is shown in both set theory notation and python making it much easier for a programmer to understand the theory.
May 21, 2011 rated it really liked it

قرأت بعض الفصول منه مجبرة لامتحاني يوم الغد :(
أسلوب الكتاب سلس جداً ..
Muhammad al-Khwarizmi
Really very decent introduction to this particularly library. A big caveat is that it contains a fairly large number of typos, even really obvious ones like "ibigrams", and includes some code that no longer functions with the current iteration of NLTK. Another issue, at least from my point of view, is that it isn't really geared towards a streamlined approach to using NLTK as a tool for text mining, with its numerous digressions into how to use Python for those entirely unfamiliar with it, as a ...more
Jun 21, 2017 rated it really liked it
This excellent work moves the novice from the basics of natural language processing (NLP) into advanced topics with dexterity. NLP is the discipline of interpreting language as humans produce it with computational tools that computers require. By the time you complete this book you will be able to incorporate NLP into your data science workflow.

There are several things I love about this book. It strikes an excellent balance between theory and applications. It provides compelling use cases along
Ankit Solanki
Dec 03, 2017 rated it liked it
Shelves: read-in-college
The books even though lost generality as a whole but still shows the working of NLP algorithms much clearly then other website or blogs, it certainly give me a better vision of natural language processing. The approach of this book was to state and explain with a hell lot of examples and it was indeed a good idea. The last 2 chapters were really complex and hard to understand but I'm sure if I'll read those topics again and the insight gained in this book will help me a lot in it. If you are als ...more
Shubhang Goswami
Apr 22, 2018 rated it really liked it
A guide book on the NLTK toolkit that allows you to dissect language and make a computer understand language.

The authors build up from very simple models to complex ones as the book progresses, clearly laying down a story in front of us.

If you are well verse with python you can skip the first 4 chapters and head straight to chapter 5. I liked this book and it gave me an idea of how google assistant might parse data when I ask it to do something for me. Makes you look at language differently.

Mar 06, 2018 rated it liked it
A solid resource that feels a bit overdue for an update. Much of the core linguistic information is still relevant I am sure, but there is no coverage of newer ML techniques (word embeddings, RNNs, etc.), and the Python NLTK library itself has been updated extensively enough since this was published to render many of the code examples incompatible with the current version. For those pursuing grammar-based approaches to NLP, though, this should still prove a useful reference.
Jesús Navarro
May 11, 2017 rated it really liked it
A very clear, simple and comprehensive book on the fundamentals of NLP, the techniques and theory involved, with practical examples. Covers tokenization, tagging, parsing, information extraction, classification, syntactic and semantic analysis.
Vilém Zouhar
Jan 15, 2018 rated it it was ok
My disappointment has roots in my expectation of theoretical introduction to Natural Language Processing. I'm not pressing this book is not enjoable, but that's not the case only if you want 500 pages of Python nltk examples.
Wasim Khan
Mar 20, 2018 rated it really liked it
This book introduces both Natural Language Processing Toolkit and Natural Language Processing and it's a good book at that. Both theory and code examples are thrown in good measure. It's a must if you want to have NLP concepts before jumping to NLP packages.
Fatma Fatma
Apr 25, 2018 rated it it was amazing
good practice for NLP scientist
Ivan Atanasov
Oct 16, 2017 rated it liked it
It explain the basic concept about NLP toolkit.
David Rauschenbach
Sep 07, 2014 rated it it was amazing
In my 24 years as a software engineer, this is the best technical book I have ever read. I It represents the state of the art in technical writing style. Where most technical books age quickly, this one is surprisingly open-ended, and tied to an external developer toolkit that is both wonderful and growing. The subject matter is structured (readable as a narrative, then good for reference), thoroughly treated (by Stanford alumns), and grounded in historical references and philosophical themes. I ...more
Dave Peticolas
May 10, 2014 rated it liked it
A wonderful introduction to natural language processing using the NLTK toolkit. This book also serves as an introduction to Python for those new to the language (and to programming, though the pace is pretty fast). And for those like me, not new to Python but totally ignorant of NLP, it contains a wealth of interesting material. Finally, the examples showcase the elegance of Python as a language for text processing.
K.C. Hopson
Comprehensive intro

While, I was not interested in learning Python, I did want to learn the state of the art in NLP. This book does the latter better than anything this side of a college textbook, from what I can see. If you want to learn Python, this book is an incredible start also!
Mar 15, 2016 rated it it was amazing
full of interesting ideas will walk you through basic python development, text processing and machine learning. There is a lot to take in with this book, i can see myself returning to it in the future to use it as a reference.

some of the examples need tweaking since the book is from 2009 some things have changed within the nltk library.
Christopher Käck
Jun 27, 2013 rated it really liked it
Nice introduction to NLP.
It also serves as a intro to Python for some reason. Probably nice for someone new to the language.

The best part is the introduction to the Natural Language Toolkit (nltk) python library which is a great way to get started with and explore NLP.
Aug 12, 2013 rated it it was amazing
Excellent. Certainly wish I had this book when I took "Natural Language Processing" back in grad school. Good intro to the topic of NLP, and you wind up being able to actually do things in Python when you're finished.
Apr 11, 2016 rated it liked it
Shelves: technical
Pretty neat stuff! Good to know about this Python package, and I'll definitely pick this back up next time I have a relevant problem. Not for the total beginner, though - not the least because of some significant, head-scratching bugs in the code.
Daniel Svoboda
Jul 27, 2015 rated it it was amazing  ·  review of another edition
Really good and concise introduction to Natural Language Processing and the indispensable NLTK library for doing your own NLP projects. O'Reilly has again given a great technical book that reads like literature.
Vincent Russo
Nov 10, 2015 rated it it was amazing
Shelves: data-science
This series of books are great. For the readers that already known Python, it's very clear which sections of the book can be glossed over to focus on the NLP portions. Lots of very practical examples that make use of the NLTK corpus, a resource that is actually quite useful to test on.
May 31, 2012 rated it it was amazing
Such an interesting problem, and such a fun programming language. The NLTK looks great and I certainly hope to put it to good use soon. This book was very clear and easy to follow, and is a great resource I'm sure I'll be referring back to before too long.
Ur Salem
Jan 08, 2015 marked it as to-read
Shelves: oreilly
Kiran Gangadharan
3 stars because I only skimmed it and so not eligible to provide a proper review.

That being said, the writing is clear with a lot of code examples to try out.
Apr 06, 2016 rated it it was amazing
Shelves: 2016_tech, big-data
It is a very nice book on NLP. I found it very well structured and there are a bunch of following tasks that can be done and a couple of follow up readings. It is easy to read !
Christofer Garner
Data needs context.
Lewis Cawthorne
Oct 19, 2011 rated it liked it
Fine book, but very slow if you know any python.
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“>>> puzzle_letters = nltk.FreqDist('egivrvonl') >>> obligatory = 'r' >>> wordlist = nltk.corpus.words.words() >>> [w for w in wordlist if len(w) >= 6 ...                      and obligatory in w ...                      and nltk.FreqDist(w) <= puzzle_letters] ['glover', 'gorlin', 'govern', 'grovel', 'ignore', 'involver', 'lienor', 'linger', 'longer', 'lovering', 'noiler', 'overling', 'region', 'renvoi', 'revolving', 'ringle', 'roving', 'violer', 'virole']” 1 likes
“>>> wn.synset('car.n.01').definition 'a motor vehicle with four wheels; usually propelled by an internal combustion engine' >>> wn.synset('car.n.01').examples ['he needs a car to get to work']” 0 likes
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