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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
Languages
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

Topic Modeling

In this chapter, we will cover topic modeling, or the classification of topics present in a corpus of text. Topic modeling is a very useful technique that can give us an idea about which topics appear in a document set. For example, topic modeling is used for trend discovery on social media. Also, in many cases, it is useful to do topic modeling as part of the preliminary data analysis of a dataset to understand which topics appear in it.

There are many different algorithms available to do this. All of them try to find similarities between different texts and put them into several clusters. These different clusters indicate different topics.

You will learn how to create and use topic models via various techniques with the BBC news dataset in this chapter. This dataset has news that falls within the following topics: politics, sport, business, tech, and entertainment. Thus, we know that in each case, we need to have five topic clusters. This is not going to be the...

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