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The Handbook of NLP with Gensim

The Handbook of NLP with Gensim

By : Chris Kuo
5 (6)
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The Handbook of NLP with Gensim

The Handbook of NLP with Gensim

5 (6)
By: Chris Kuo

Overview of this book

Navigating the terrain of NLP research and applying it practically can be a formidable task made easy with The Handbook of NLP with Gensim. This book demystifies NLP and equips you with hands-on strategies spanning healthcare, e-commerce, finance, and more to enable you to leverage Gensim in real-world scenarios. You’ll begin by exploring motives and techniques for extracting text information like bag-of-words, TF-IDF, and word embeddings. This book will then guide you on topic modeling using methods such as Latent Semantic Analysis (LSA) for dimensionality reduction and discovering latent semantic relationships in text data, Latent Dirichlet Allocation (LDA) for probabilistic topic modeling, and Ensemble LDA to enhance topic modeling stability and accuracy. Next, you’ll learn text summarization techniques with Word2Vec and Doc2Vec to build the modeling pipeline and optimize models using hyperparameters. As you get acquainted with practical applications in various industries, this book will inspire you to design innovative projects. Alongside topic modeling, you’ll also explore named entity handling and NER tools, modeling procedures, and tools for effective topic modeling applications. By the end of this book, you’ll have mastered the techniques essential to create applications with Gensim and integrate NLP into your business processes.
Table of Contents (24 chapters)
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1
Part 1: NLP Basics
5
Part 2: Latent Semantic Analysis/Latent Semantic Indexing
9
Part 3: Word2Vec and Doc2Vec
12
Part 4: Topic Modeling with Latent Dirichlet Allocation
18
Part 5: Comparison and Applications

LDA Visualization

Topic modeling classifies a large volume of corpora into topics, and each topic has a set of distinct words. It produces very rich information for each topic. The next challenge is how to present the rich information. This challenge is a research topic in the development of NLP.

The good news is that several visual tools have provided the solution, including pyLDAvis, which we will cover in this chapter. We will first discuss the gap between hard topic modeling and soft human comprehension. Then we will learn how to use pyLDAvis.

We will cover the following topics:

  • Designing an infographic
  • Data visualization with pyLDAvis

By the end of this chapter, you will be able to visualize an LDA model using interactive infographics to explain model insights. The design of pyLDAvis infographics has even influenced the visualization of BERTopic model outcomes, which we will practice in Chapter 14, LDA and BERTopic.

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