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Python Natural Language Processing Cookbook

You're reading from Python Natural Language Processing Cookbook Over 50 recipes to understand, analyze, and generate text for implementing language processing tasks

Product type Paperback

Published in Mar 2021

Publisher Packt

ISBN-13 9781838987312

Length 284 pages

Edition 1st Edition

Languages

Processing

Tools

Processing

Concepts

Mobile Application Development

Author (1):

Zhenya Antić

View More author details

Table of Contents (10) Chapters

Preface

1. Chapter 1: Learning NLP Basics

2. Chapter 2: Playing with Grammar FREE CHAPTER

3. Chapter 3: Representing Text – Capturing Semantics

4. Chapter 4: Classifying Texts

5. Chapter 5: Getting Started with Information Extraction

6. Chapter 6: Topic Modeling

7. Chapter 7: Building Chatbots

8. Chapter 8: Visualizing Text Data

9. Other Books You May Enjoy

Chapter 3: Representing Text – Capturing Semantics

Representing the meaning of words, phrases, and sentences in a form that's understandable to computers is one of the pillars of NLP processing. Machine learning, for example, represents each data point as a fixed-size vector, and we are faced with the question of how to turn words and sentences into vectors. Almost any NLP task starts with representing the text in some numeric form, and this chapter will show several ways of doing that. Once you've learned how to represent text as vectors, you will be able to perform tasks such as classification, which will be described in later chapters.

We will also learn how to turn phrases such as fried chicken into vectors, how to train a word2vec model, and how to create a small search engine with semantic search.

The following recipes will be covered in this chapter:

Putting documents into a bag of words
Constructing the N-gram model
Representing texts...

The rest of the chapter is locked

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Authors (1)

Zhenya Antić

Zhenya Antić

Zhenya Antić, Ph.D. is an expert in AI and NLP. She is currently the Director of AI Automation at Arch Insurance, where she leads initiatives in Intelligent Document Processing and applies various AI solutions to complex problems. With extensive consulting experience, Zhenya has worked on numerous NLP projects with various companies. She holds a Ph.D. in Linguistics from the University of California, Berkeley, and a B.S. in Computer Science from the Massachusetts Institute of Technology.

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