- Quickly get to grips with Natural Language Processing - with Tokenizing Text, WordNet, and beyond
- Learn how to replace and correct words to improve search engine results
- Categorize documents and pieces of text and assign class labels
- Part of Packt's Cookbook series: Each recipe is a carefully organized sequence of instructions to complete the task as efficiently as possible
In Detail
Natural Language Processing is used everywhere - in search engines, spell checkers, mobile phones, computer games - even your washing machine. Python's Natural Language Toolkit (NLTK) suite of libraries has rapidly emerged as one of the most efficient tools for Natural Language Processing. You want to employ nothing less than the best techniques in Natural Language Processing - and this book is your answer.
Python Text Processing with NLTK 2.0 Cookbook is your handy and illustrative guide, which will walk you through all the Natural Language Processing techniques in a step-by-step manner. It will demystify the advanced features of text analysis and text mining using the comprehensive NLTK suite.
What you will learn from this book
- Learn Text categorization and Topic identification
- Use Stemming and Lemmatization to go beyond the usual spell checker
- Replace negations with antonyms in your text
- Tokenize words into lists of sentences and words, and gain an insight into WordNet
- Train and manipulate different types of classifiers
- Automatically correct spelling with Enchant
- Translate text using Babelfish
Approach
The learn-by-doing approach of this book will enable you to dive right into the heart of text processing from the very first page. Each recipe is carefully designed to fulfill your appetite for Natural Language Processing. Packed with numerous illustrative examples and code samples, it will make the task of using the NLTK for Natural Language Processing easy and straightforward..
Who this book is written for
This book is for Python programmers who want to quickly get to grips with using the NLTK for Natural Language Processing. Familiarity with basic text processing concepts is required. Programmers experienced in the NLTK will also find it useful. Students of linguistics will find it invaluable.
Jacob Perkins
Jacob Perkins has been an avid user of open source software since high school, when he first built his own computer and didn't want to pay for Windows. At one point he had 5 operating systems installed, including RedHat Linux, OpenBSD, and BeOS.
While at Washington University in St. Louis, Jacob took classes in Spanish, poetry writing, and worked on an independent study project that eventually became his Master's Project: WUGLE - a GUI for manipulating logical expressions. In his free time, he wrote the Gnome2 version of Seahorse (a GUI for encryption and key management), which has since been translated into over a dozen languages and is included in the default Gnome distribution.
After getting his MS in Computer Science, Jacob tried to start a web development studio with some friends, but since no-one knew anything about web development, it didn't work out as planned. Once he'd actually learned web development, he went off and co-founded another company called Weotta, which sparked his interest in Machine Learning and Natural Language Processing.
Jacob is currently the CTO / Chief Hacker for Weotta and blogs about what he's learned along the way at streamhacker.com/. He is also applying this knowledge to produce text processing APIs and demos at text-processing.com/.This book is a synthesis of his knowledge on processing text using Python, NLTK, and more.
