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Python Natural Language Processing Cookbook

You're reading from   Python Natural Language Processing Cookbook Over 50 recipes to understand, analyze, and generate text for implementing language processing tasks

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Product type Paperback
Published in Mar 2021
Publisher Packt
ISBN-13 9781838987312
Length 284 pages
Edition 1st Edition
Languages
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Author (1):
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Zhenya Antić Zhenya Antić
Author Profile Icon Zhenya Antić
Zhenya Antić
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Toc

Table of Contents (10) 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: Building Chatbots 8. Chapter 8: Visualizing Text Data 9. Other Books You May Enjoy

LDA topic modeling with gensim

In the previous section, we saw how to create an LDA model with the sklearn package. In this recipe, we will create an LDA model using the gensim package.

Getting ready

We will be using the gensim package, which can be installed using the following command:

pip install gensim

How to do it…

We will load the data, clean it, preprocess it in a similar fashion to the previous recipe, and then create the LDA model. The steps for this recipe are as follows:

  1. Perform the necessary imports:
    import re
    import pandas as pd
    from gensim.models.ldamodel import LdaModel
    import gensim.corpora as corpora
    from gensim.utils import simple_preprocess
    import matplotlib.pyplot as plt
    from pprint import pprint
    from Chapter06.lda_topic import stopwords, bbc_dataset, clean_data
  2. Define the function that will preprocess the data. It uses the clean_data function from the previous recipe:
    def preprocess(df):
        df = clean_data(df...
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