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Python Natural Language Processing Cookbook

You're reading from   Python Natural Language Processing Cookbook Over 60 recipes for building powerful NLP solutions using Python and LLM libraries

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Product type Paperback
Published in Sep 2024
Publisher Packt
ISBN-13 9781803245744
Length 312 pages
Edition 2nd Edition
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Concepts
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Authors (2):
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Saurabh Chakravarty Saurabh Chakravarty
Author Profile Icon Saurabh Chakravarty
Saurabh Chakravarty
Zhenya Antić Zhenya Antić
Author Profile Icon Zhenya Antić
Zhenya Antić
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Toc

Table of Contents (13) Chapters Close

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: Visualizing Text Data 8. Chapter 8: Transformers and Their Applications 9. Chapter 9: Natural Language Understanding 10. Chapter 10: Generative AI and Large Language Models 11. Index 12. Other Books You May Enjoy

Visualizing Text Data

This chapter is dedicated to creating visualizations for the different aspects of NLP work, much of which we have done in previous chapters. Visualizations are important when working with NLP tasks, as they help us to easier see the big picture of the work accomplished.

We will create different types of visualizations, including visualizations of grammar details, parts of speech, and topic models. After working through this chapter, you will be well equipped to create compelling images to show and explain the outputs of various NLP tasks.

These are the recipes you will find in this chapter:

  • Visualizing the dependency parse
  • Visualizing parts of speech
  • Visualizing NER
  • Creating a confusion matrix plot
  • Constructing word clouds
  • Visualizing topics from Gensim
  • Visualizing topics from BERTopic
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