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The Handbook of NLP with Gensim

You're reading from   The Handbook of NLP with Gensim Leverage topic modeling to uncover hidden patterns, themes, and valuable insights within textual data

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Product type Paperback
Published in Oct 2023
Publisher Packt
ISBN-13 9781803244945
Length 310 pages
Edition 1st Edition
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Author (1):
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Chris Kuo Chris Kuo
Author Profile Icon Chris Kuo
Chris Kuo
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Toc

Table of Contents (24) Chapters Close

Preface 1. Part 1: NLP Basics
2. Chapter 1: Introduction to NLP FREE CHAPTER 3. Chapter 2: Text Representation 4. Chapter 3: Text Wrangling and Preprocessing 5. Part 2: Latent Semantic Analysis/Latent Semantic Indexing
6. Chapter 4: Latent Semantic Analysis with scikit-learn 7. Chapter 5: Cosine Similarity 8. Chapter 6: Latent Semantic Indexing with Gensim 9. Part 3: Word2Vec and Doc2Vec
10. Chapter 7: Using Word2Vec 11. Chapter 8: Doc2Vec with Gensim 12. Part 4: Topic Modeling with Latent Dirichlet Allocation
13. Chapter 9: Understanding Discrete Distributions 14. Chapter 10: Latent Dirichlet Allocation 15. Chapter 11: LDA Modeling 16. Chapter 12: LDA Visualization 17. Chapter 13: The Ensemble LDA for Model Stability 18. Part 5: Comparison and Applications
19. Chapter 14: LDA and BERTopic 20. Chapter 15: Real-World Use Cases 21. Assessments 22. Index 23. Other Books You May Enjoy

Part 4: Topic Modeling with Latent Dirichlet Allocation

Topic modeling can produce rich information for each topic. In this part, you will learn about a milestone topic modeling technique – the Latent Dirichlet Allocation. There are several fundamental concepts applied in LDA, thus this part introduces the key concepts in different chapters.

First, you will learn about the discrete distribution family from the simple to more generalized forms, including the Dirichlet distribution. With that, this part presents the intuition and architecture of an LDA. With the theoretical understanding, you will build LDA with Gensim.

The next question is how to visualize and communicate the results. Here, you will appreciate the design of the infographic for LDA. Further, you will understand why LDA may not produce reliable results and the advance to Ensemble LDA for model stability.

This part contains the following chapters:

  • Chapter 9, Understanding Discrete Distributions...
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