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Textbook in PDF format

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