Perkins Python Text Processing with NLTK 2.0 Cookbook: LITE

Python Text Processing with NLTK 2.0 Cookbook: LITE
1. Auflage 2025
ISBN: 978-1-84951-639-6
Verlag: De Gruyter
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 92 Seiten

Key FeaturesBook DescriptionThe 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. 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.What you will learn - 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
Who this book is for

Autoren/Hrsg.

Perkins, Jacob

Fachgebiete

• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein

Über Autor(innen)

Perkins Jacob :

Jacob Perkins is the cofounder and CTO of Weotta, a local search company. Weotta uses NLP and machine learning to create powerful and easy-to-use natural language search for what to do and where to go. He is the author of Python Text Processing with NLTK 2.0 Cookbook, Packt Publishing, and has contributed a chapter to the Bad Data Handbook, O'Reilly Media. He writes about NLTK, Python, and other technology topics at http://streamhacker.com. To demonstrate the capabilities of NLTK and natural language processing, he developed http://text-processing.com, which provides simple demos and NLP APIs for commercial use. He has contributed to various open source projects, including NLTK, and created NLTK-Trainer to simplify the process of training NLTK models. For more information, visit https://github.com/japerk/nltk-trainer.