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Feature Engineering Made Easy

You're reading from   Feature Engineering Made Easy Identify unique features from your dataset in order to build powerful machine learning systems

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781787287600
Length 316 pages
Edition 1st Edition
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Authors (2):
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Divya Susarla Divya Susarla
Author Profile Icon Divya Susarla
Divya Susarla
Sinan Ozdemir Sinan Ozdemir
Author Profile Icon Sinan Ozdemir
Sinan Ozdemir
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Table of Contents (10) Chapters Close

Preface 1. Introduction to Feature Engineering 2. Feature Understanding – What's in My Dataset? FREE CHAPTER 3. Feature Improvement - Cleaning Datasets 4. Feature Construction 5. Feature Selection 6. Feature Transformations 7. Feature Learning 8. Case Studies 9. Other Books You May Enjoy

Text-specific feature construction

Until this point, we have been working with categorical and numerical data. While our categorical data has come in the form of a string, the text has been part of a single category. We will now dive deeper into longer—form text data. This form of text data is much more complex than single—category text, because we now have a series of categories, or tokens. 

Before we get any further into working with text data, let's make sure we have a good understanding of what we mean when we refer to text data. Consider a service like Yelp, where users write up reviews of restaurants and businesses to share their thoughts on their experience. These reviews, all written in text format, contain a wealth of information that would be useful for machine learning purposes, for example, in predicting the best restaurant to visit. 

In...

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