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Hit the ground running with this in-depth introduction to the NLP skills and techniques that allow your computers to speak human.

In Getting Started with Natural Language Processing you’ll learn about:

  • Fundamental concepts and algorithms of NLP
  • Useful Python libraries for NLP
  • Building a search algorithm
  • Extracting information from raw text
  • Predicting sentiment of an input text
  • Author profiling
  • Topic labeling
  • Named entity recognition

Getting Started with Natural Language Processing is an enjoyable and understandable guide that helps you engineer your first NLP algorithms. Your tutor is Dr. Ekaterina Kochmar, lecturer at the University of Bath, who has helped thousands of students take their first steps with NLP. Full of Python code and hands-on projects, each chapter provides a concrete example with practical techniques that you can put into practice right away. If you’re a beginner to NLP and want to upgrade your applications with functions and features like information extraction, user profiling, and automatic topic labeling, this is the book for you.

About the Technology
From smart speakers to customer service chatbots, apps that understand text and speech are everywhere. Natural language processing, or NLP, is the key to this powerful form of human/computer interaction. And a new generation of tools and techniques make it easier than ever to get started with NLP!

About the Book
Getting Started with Natural Language Processing teaches you how to upgrade user-facing applications with text and speech-based features. From the accessible explanations and hands-on examples in this book you’ll learn how to apply NLP to sentiment analysis, user profiling, and much more. As you go, each new project builds on what you’ve previously learned, introducing new concepts and skills. Handy diagrams and intuitive Python code samples make it easy to get started—even if you have no background in machine learning!

What's Inside
  • Fundamental concepts and algorithms of NLP
  • Extracting information from raw text
  • Useful Python libraries
  • Topic labeling
  • Building a search algorithm


About the Reader
You’ll need basic Python skills. No experience with NLP required.

About the Author
Ekaterina Kochmar is a lecturer at the Department of Computer Science of the University of Bath, where she is part of the AI research group.

Quotes
An accessible entry point. Learn key NLP concepts by building real-world projects.
- Samantha Berk, AdaptX

A well-written, pragmatic book.
- James Richard Woodruff, SAIC

The best NLP resource.
- Najeeb Arif, ThoughtWorks

Get started with NLP and understand its fundamentals.
- Walter Alexander Mata López, University of Colima

Makes a difficult subject easy to understand.
- Tanya Wilke, .NET Engineer

Table of Contents

  1. inside front cover
  2. Getting Started with Natural Language Processing
  3. Copyright
  4. dedication
  5. contents
  6. front matter
  7. 1 Introduction
  8. 2 Your first NLP example
  9. 3 Introduction to information search
  10. 4 Information extraction
  11. 5 Author profiling as a machine-learning task
  12. 6 Linguistic feature engineering for author profiling
  13. 7 Your first sentiment analyzer using sentiment lexicons
  14. 8 Sentiment analysis with a data-driven approach
  15. 9 Topic analysis
  16. 10 Topic modeling
  17. 11 Named-entity recognition
  18. Appendix A Installation instructions
  19. index
  20. inside back cover
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