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Python Book:Natural Language Processing with Python

| February 4, 2013 | 1 Comment
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This book offers a highly accessible introduction to Natural Language Processing, the field that underpins a variety of language technologies, ranging from predictive text and email filtering to automatic summarization and translation. With Natural Language Processing with Python, you’ll learn how to write Python programs to 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, 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

Perfect for individual study, or as a classroom and workshop textbook, 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, documenting endangered languages, or if you are simply curious to have a programmer’s perspective on how human language works, you will find Natural Language Processing with Python both fascinating and immensely useful.

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.

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Category: Python Book

About the Author ()

My name is John Link.I am 26 years old. My major is Computer science and technology. I am a junior programmer with Python.

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