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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

Product type Paperback

Published in Mar 2021

Publisher Packt

ISBN-13 9781838987312

Length 284 pages

Edition 1st Edition

Languages

Processing

Tools

Processing

Concepts

Mobile Application Development

Author (1):

Zhenya Antić

View More author details

Table of Contents (10) Chapters

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

Getting the dataset and evaluation baseline ready

Classifying texts is a classic NLP problem. This NLP task involves assigning a value to a text, for example, a topic or a sentiment, and any such task requires evaluation. In this recipe, we will load a dataset, prepare it for processing, and create an evaluation baseline. The recipe builds on some of the recipes from Chapter 3, Representing Text: Capturing Semantics, where we used different tools to represent text in a computer-readable form.

Getting ready

For most recipes in this chapter, we will use the BBC News dataset, which contains text from five topics: business, entertainment, politics, sport, and tech. The dataset is located in the bbc-text.csv file in this chapter's GitHub directory.

In this recipe, we will need two additional packages, numpy and sklearn. Install them using pip:

pip install numpy
pip install sklearn

How to do it…

In this recipe, we will be classifying just two of the five topics...

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Authors (1)

Zhenya Antić

Zhenya Antić

Zhenya Antić, Ph.D. is an expert in AI and NLP. She is currently the Director of AI Automation at Arch Insurance, where she leads initiatives in Intelligent Document Processing and applies various AI solutions to complex problems. With extensive consulting experience, Zhenya has worked on numerous NLP projects with various companies. She holds a Ph.D. in Linguistics from the University of California, Berkeley, and a B.S. in Computer Science from the Massachusetts Institute of Technology.

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