|Author:||Edward Loper,Steven Bird|
|Publisher:||O'Reilly Media; 1 edition (July 10, 2009)|
|Category:||Technologies and Computers|
|Other formats:||azw lrf lrf docx|
Steven Bird, Ewan Klein, and Edward Loper
Steven Bird, Ewan Klein, and Edward Loper. 3. Processing Raw Text. 4. Writing Structured Programs. 5. Categorizing and Tagging Words (minor fixes still required)
Printed in the United States of America.
Its target audience is a narrow one. It assumes a working familiarity with Python. It's true that an experienced programmer could learn Python along the way, but getting the most from the code examples and walkthrough explanations requires enough familiarity to "think" in Python.
Analyze linguistic structure in text, including parsing and semantic analysis.
Unless noted otherwise, all solutions are my own and represent original material
Unless noted otherwise, all solutions are my own and represent original material.
In the humanities, the work on corpora is gaining increasing prominence. Within industry, people need NLP for market analysis, web software development to name a few examples.
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. 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.
Other readers will always be interested in your opinion of the books you've read. Whether you've loved the book or not, if you give your honest and detailed thoughts then people will find new books that are right for them. 1. Design, creation, and analysis of Czech corpora for structural metadata extraction from speech.
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 analysisAccess popular linguistic databases, including WordNet and treebanksIntegrate techniques drawn from fields as diverse as linguistics and artificial intelligenceThis 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.