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 using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you:

• Extract information from unstructured text, either to guess the topic or identify "named entities"

• Analyze linguistic structure in text, including parsing and semantic analysis

• Access popular linguistic databases, including WordNet and treebanks

• Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence

This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.

Amazon.com® Reader Reviews (Ranked by Helpfulness)

Average Amazon.com® Rating:  Based on 7 Ratings

Good book, great library - 2009-09-21
Reviewer Rating:
Buy this book only if you:
1. Know the basics of natural language processing (NLP) or linguistics;
2. Know the Python programming language or you're willing to learn it;
3. Are using the NLTK library or plan to do so.

NLTK is a Python library that offers many standard NLP tools (tokenizers, POS taggers, parsers, chunkers and others). It comes with samples of several dozens of text corpora typically used in NLP applications, as well as with interfaces to dictionary-like resources such as WordNet and VerbNet. No FrameNet, though. NLTK is well documented, so you might not need this book initially. However, it definitely helps to have it on your desk if you are serious about using NLTK.

The first chapters are a bit messy, as they attempt to introduce all three themes (NLP, NLTK and Python) together. Beginners may have some difficulty sorting things out. By the time you reach the WordNet section, you either got lost in the forest, realize that you would never understand this topic without the book, or both. However, if you are a bit patient and try out all simple code examples, you'll make it eventually. In my opinion, NLTK remains the simplest, most elegant and well rounded library of its kind.

Suitable for NLP people interested in learning Python and NLTK - 2009-08-28
Reviewer Rating:
There are three kinds of people who might think this book could be useful:

1. Natural language processing (NLP) researchers and students who want a learn a solid programming tool to help them with their work.
2. Python programmers who want to find out more about NLP.
3. Newbies in both Python and NLP who just think the topic sounds cool and those whales on the cover are kinda cute.

In my opinion, the only kind that will find this book suitable and useful is (1). If you're familiar with Python and know no NLP it won't help you much, because it doesn't really teach NLP. It shows a few domains of this vast field, with nice code examples and all, but you should probably start with some introductory textbook on the subject or a course. You won't really learn NLP here.

The book's focus is mostly on the NLTK library written in Python by the authors. This library implements many NLP algorithms and comes with lots of data for testing and training. Almost no algorithms are implemented in the book - some are explained, and the code always imports the required modules from NLTK and shows their usage. The Python code is well-written and clean.

To conclude, if you're a NLP researcher or student, this is a very good book to read. Especially if you plan to start working with NLTK (which seems like a mature and powerful tool) - this book will serve as a great introduction. If you have other interests, this is probably not the right book.

A good overview - 2009-09-12
Reviewer Rating:
I've only made it through the first half of the book, but here's what I think so far. It's a good book with a lot of overview information on the types of thinks that can be done with NLP today. I've certainly learned a lot. What I was disappointed by was the lack of description of the inner workings of many of the algorithms. They just give you a library and expect you to treat it as a black box. If you don't want to use their library, you have a long ways to go for real understanding.

Fantastic must-read intro to Python & NLP using NLTK - 2009-08-05
Reviewer Rating:
If you have any need for Natural Language Processing - this book is the one you must read. I've bought & read the famous textbooks on the subject, but these give you just the theory & math. This book however gives you the practical know-how in order to get you started & running, in no time. It does this by using the programming language of choice for this domain (Python) & the framework of choice for doing the actual work (NLTK), which the authors have developed.
Really fun to read & very very useful, for programmers as well as anyone wishing to process texts automatically. Good also for non-programmers, as it gently introduces the programming idioms required to get the work done, & does it really well!

Tardy but good - 2009-11-15
Reviewer Rating:
The book I ordered took quite a long time to arrive, but it was in great shape when it did come.

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