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The Natural Language Processing Workshop

You're reading from  The Natural Language Processing Workshop

Product type Book
Published in Aug 2020
Publisher Packt
ISBN-13 9781800208421
Pages 452 pages
Edition 1st Edition
Languages
Authors (6):
Rohan Chopra Rohan Chopra
Profile icon Rohan Chopra
Aniruddha M. Godbole Aniruddha M. Godbole
Profile icon Aniruddha M. Godbole
Nipun Sadvilkar Nipun Sadvilkar
Profile icon Nipun Sadvilkar
Muzaffar Bashir Shah Muzaffar Bashir Shah
Profile icon Muzaffar Bashir Shah
Sohom Ghosh Sohom Ghosh
Profile icon Sohom Ghosh
Dwight Gunning Dwight Gunning
Profile icon Dwight Gunning
View More author details

Table of Contents (10) Chapters

Preface
1. Introduction to Natural Language Processing 2. Feature Extraction Methods 3. Developing a Text Classifier 4. Collecting Text Data with Web Scraping and APIs 5. Topic Modeling 6. Vector Representation 7. Text Generation and Summarization 8. Sentiment Analysis Appendix

5. Topic Modeling

Activity 5.01: Topic-Modeling Jeopardy Questions

Solution

Let's perform topic modeling on the dataset of Jeopardy questions:

  1. Open a Jupyter Notebook.
  2. Insert a new cell and add the following code to import pandas and other libraries:
    import numpy as np
    import spacy
    nlp = spacy.load('en_core_web_sm')
    import pandas as pd
    pd.set_option('display.max_colwidth', 800)
  3. After downloading the data, you can extract it and place at the location below. Then load the Jeopardy CSV file into a pandas DataFrame. Insert a new cell and add the following code:
    JEOPARDY_CSV =  '../data/jeopardy/Jeopardy.csv'
    questions = pd.read_csv(JEOPARDY_CSV)
    questions.columns = [x.strip() for x in questions.columns]
  4. The data in the DataFrame is not clean. In order to clean it, remove records that have missing values in the Question column. Add the following code to do this:
    questions = questions.dropna(subset=['Question'])
  5. Find...
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