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Natural Language Processing Fundamentals

You're reading from   Natural Language Processing Fundamentals Build intelligent applications that can interpret the human language to deliver impactful results

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Product type Paperback
Published in Mar 2019
Publisher
ISBN-13 9781789954043
Length 374 pages
Edition 1st Edition
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Authors (2):
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Dwight Gunning Dwight Gunning
Author Profile Icon Dwight Gunning
Dwight Gunning
Sohom Ghosh Sohom Ghosh
Author Profile Icon Sohom Ghosh
Sohom Ghosh
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Toc

Table of Contents (10) Chapters Close

Preface 1. Introduction to Natural Language Processing FREE CHAPTER 2. Basic Feature Extraction Methods 3. Developing a Text classifier 4. Collecting Text Data from the Web 5. Topic Modeling 6. Text Summarization and Text Generation 7. Vector Representation 8. Sentiment Analysis Appendix

5. Topic Modeling

Learning Objectives

By the end of this chapter, you will be able to:

  • Describe topic modelling and its various use cases
  • Describe topic modeling algorithms
  • Describe the workings of LSA and LDA
  • Describe topic fingerprinting
  • Implement topic modeling using LSA and LDA

In this chapter, you will learn about different topic modeling algorithms and how we can use them to perform topic modeling on any dataset.

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