Natural Language Processing Using Python Cover

Natural Language Processing Using Python

by Yuli Vasiliev
April 2020 (estimated), 280 pp.
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Download Chapter 2: The Text-Processing Pipeline

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Natural Language Processing Using Python is an introduction to natural language processing (NLP), the task of converting human language into data that a computer can process. The book uses spaCy, a leading Python library for NLP, to guide readers through common NLP tasks related to generating and understanding human language with code. It addresses problems like understanding a user's intent, continuing a conversation with a human, and maintaining the state of a conversation. It also teaches you how to connect an NLP script to a messaging app, store user data in a database to fill in a form, and customize your own statistical models to improve text processing. This book will give you the foundation you need to build your own chatbots, ticket-ordering apps, text-condensing scripts, and more.

  • Uses examples and problems applicable to actual NLP apps
  • Includes exercises to help the reader move beyond each lesson
  • Covers foundational techniques that readers can implement in other NLP libraries, not just in spaCy
Author Bio 

Yuli Vasiliev is a programmer, freelance author, and consultant currently specializing in open source development, Oracle database technologies, and more recently natural language processing (NLP).

Currently, he works as a consultant in the bot project Porphyry run by Igor Shabalin. The bot implements various NLP techniques used to give meaningful responses to user questions. The demonstration version of this bot can be accessed at @Porphyry_bot in Telegram.

Table of contents 


Chapter 1: How Natural Language Processing Works
Chapter 2: The Text-Processing Pipeline
Chapter 3: Working with Container Objects and Customizing spaCy
Chapter 4: Extracting and Using Linguistic Features
Chapter 5: Working with Word Vectors
Chapter 6: Finding Patterns and Walking Dependency Trees
Chapter 7:Visualizations
Chapter 8: Intent Recognition
Chapter 9: Storing User Input in a Database
Chapter 10: Training Models
Chapter 11: Deploying Your Own Chatbot
Chapter 12: Implementing Web Data and Processing Images
Linguistic Primer