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Python Machine Learning Cookbook

You're reading from   Python Machine Learning Cookbook Over 100 recipes to progress from smart data analytics to deep learning using real-world datasets

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781789808452
Length 642 pages
Edition 2nd Edition
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Authors (2):
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Giuseppe Ciaburro Giuseppe Ciaburro
Author Profile Icon Giuseppe Ciaburro
Giuseppe Ciaburro
Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
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Toc

Table of Contents (18) Chapters Close

Preface 1. The Realm of Supervised Learning FREE CHAPTER 2. Constructing a Classifier 3. Predictive Modeling 4. Clustering with Unsupervised Learning 5. Visualizing Data 6. Building Recommendation Engines 7. Analyzing Text Data 8. Speech Recognition 9. Dissecting Time Series and Sequential Data 10. Analyzing Image Content 11. Biometric Face Recognition 12. Reinforcement Learning Techniques 13. Deep Neural Networks 14. Unsupervised Representation Learning 15. Automated Machine Learning and Transfer Learning 16. Unlocking Production Issues 17. Other Books You May Enjoy

Introduction

Face recognition refers to the task of identifying a person in a given image. This is different from face detection where we locate the face in a given image. During face detection, we don't care who the person is; we just identify the region of the image that contains the face. Therefore, in a typical biometric face recognition system, we need to determine the location of the face before we can recognize it.

Face recognition is very easy for humans. We seem to do it effortlessly, and we do it all the time! How do we get a machine to do the same thing? We need to understand what parts of the face we can use to uniquely identify a person. Our brain has an internal structure that seems to respond to specific features, such as edges, corners, motion, and so on. The human visual cortex combines all these features into a single coherent inference. If we want our machine...

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