Preface

Natural language processing is used everywhere, from search engines such as Google or Weotta, to voice interfaces such as Siri or Dragon NaturallySpeaking. Python's Natural Language Toolkit (NLTK) is a suite of libraries that has become one of the best tools for prototyping and building natural language processing systems.

Python 3 Text Processing with NLTK 3 Cookbook is your handy and illustrative guide, which will walk you through many natural language processing techniques in a step-by-step manner. It will demystify the dark arts of text mining and language processing using the comprehensive Natural Language Toolkit.

This book cuts short the preamble, ignores pedagogy, and lets you dive right into the techniques of text processing with a practical hands-on approach.

Get started by learning how to tokenize text into words and sentences, then explore the WordNet lexical dictionary. Learn the basics of stemming and lemmatization. Discover various ways to replace words and perform spelling corrections. Create your own corpora and custom corpus readers, including a MongoDB-based corpus reader. Use part-of-speech taggers to annotate words. Create and transform chunked phrase trees and named entities using partial parsing and chunk transformations. Dig into feature extraction and text classification for sentiment analysis. Learn how to process large amount of text with distributed processing and NoSQL databases.

This book will teach you all that and more, in a hands-on learn-by-doing manner. Become an expert in using NLTK for Natural Language Processing with this useful companion.