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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 parts of speech

In this recipe, we visualize part of speech counts. Specifically, we count the number of infinitives and past or present verbs in the book The Adventures of Sherlock Holmes. This can give us an idea about whether the text mostly talks about past or present events. We could imagine that similar tools could be used to evaluate the quality of a text; for example, a book with very few adjectives but many nouns would not work very well as a fiction book.

After working through this recipe, you will be able to use the matplotlib package to create bar plots of different verb types, which are tagged using the spacy package.

Getting ready

We will use the spacy package for text analysis and the matplotlib package to create the graph. They are part of the poetry environment and the requirements.txt file.

The notebook is located at https://github.com/PacktPublishing/Python-Natural-Language-Processing-Cookbook-Second-Edition/blob/main/Chapter07/7.2_parts_of_speech...

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