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The Natural Language Processing Workshop

You're reading from   The Natural Language Processing Workshop Confidently design and build your own NLP projects with this easy-to-understand practical guide

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Product type Paperback
Published in Aug 2020
Publisher Packt
ISBN-13 9781800208421
Length 452 pages
Edition 1st Edition
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Authors (6):
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Sohom Ghosh Sohom Ghosh
Author Profile Icon Sohom Ghosh
Sohom Ghosh
Nipun Sadvilkar Nipun Sadvilkar
Author Profile Icon Nipun Sadvilkar
Nipun Sadvilkar
Rohan Chopra Rohan Chopra
Author Profile Icon Rohan Chopra
Rohan Chopra
Muzaffar Bashir Shah Muzaffar Bashir Shah
Author Profile Icon Muzaffar Bashir Shah
Muzaffar Bashir Shah
Dwight Gunning Dwight Gunning
Author Profile Icon Dwight Gunning
Dwight Gunning
Aniruddha M. Godbole Aniruddha M. Godbole
Author Profile Icon Aniruddha M. Godbole
Aniruddha M. Godbole
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Toc

Table of Contents (10) Chapters Close

Preface
1. Introduction to Natural Language Processing 2. Feature Extraction Methods FREE CHAPTER 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

2. Feature Extraction Methods

Activity 2.01: Extracting Top Keywords from the News Article

Solution

The following steps will help you complete this Activity:

  1. Open a Jupyter Notebook.
  2. Insert a new cell and add the following code to import the necessary libraries and download the data:
    import operator
    from nltk.tokenize import WhitespaceTokenizer
    from nltk import download, stem
    # The below statement will download the stop word list 
    # 'nltk_data/corpora/stopwords/' at home directory of your computer
    download('stopwords')
    from nltk.corpus import stopwords

    The download statement will download the stop word list at nltk_data/corpora/stopwords/ into your system's home directory.

  3. Create the different types of methods to perform various NLP tasks:

    Activity 2.01.ipynb

    def load_file(file_path):
        news = ''.join\
                  ([line for line in open...
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