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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 FREE CHAPTER 2. Feature Understanding – What's in My Dataset? 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

Case study 1 - facial recognition

Our first case study will be to predict the labels for image data with a popular dataset called the Labeled Faces in the Wild dataset from the scikit-learn library. The dataset is called the Olivetti Face dataset and it comprises pictures of famous people's faces, with appropriate labels. Our task is that of facial recognition, a supervised machine learning model that is able to predict the name of the person given an image of their face.

Applications of facial recognition

Image processing and facial recognition are far-reaching. The ability to quickly discern people's faces from a crowd of people in video/images is vital for physical security as well as for giant social media...

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