Key Features
Book Description
This 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
Table of Contents
- Tokenizing Text and WordNet Basics
- Replacing and Correcting Words
- Creating Custom Corpora
- Tagging Part of Speech
- Extraction Chunks: Partial Parsing
- Transforming and Normalizing Chunks
- Extracting Features for Classifying Words and Chunks
- Distributed Processing and Handling Large Datasets
- Parsing and Matching Specific Data
- Appendix 1
Loading...
Loading...
