Perkins Python 3 Text Processing with NLTK 3 Cookbook

Python 3 Text Processing with NLTK 3 Cookbook
2. Auflage 2025
ISBN: 978-1-78216-786-0
Verlag: De Gruyter
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 304 Seiten

Key FeaturesBook DescriptionThis book is intended for Python programmers interested in learning how to do natural language processing. Maybe you’ve learned the limits of regular expressions the hard way, or you’ve realized that human language cannot be deterministically parsed like a computer language. Perhaps you have more text than you know what to do with, and need automated ways to analyze and structure that text. This Cookbook will show you how to train and use statistical language models to process text in ways that are practically impossible with standard programming tools. A basic knowledge of Python and the basic text processing concepts is expected. Some experience with regular expressions will also be helpful.What you will learn - Tokenize text into sentences, and sentences into words
- Look up words in the WordNet dictionary
- Apply spelling correction and word replacement
- Access the builtin text corpora and create your own custom corpus
- Tag words with parts of speech
- Chunk phrases and recognize named entities
- Grammatically transform phrases and chunks
- Classify text and perform sentiment analysis
Who this book is for

Autoren/Hrsg.

Perkins, Jacob

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken

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.