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Hands-On Transfer Learning with Python

You're reading from   Hands-On Transfer Learning with Python Implement advanced deep learning and neural network models using TensorFlow and Keras

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Product type Paperback
Published in Aug 2018
Publisher Packt
ISBN-13 9781788831307
Length 438 pages
Edition 1st Edition
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Authors (4):
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Nitin Panwar Nitin Panwar
Author Profile Icon Nitin Panwar
Nitin Panwar
Raghav Bali Raghav Bali
Author Profile Icon Raghav Bali
Raghav Bali
Tamoghna Ghosh Tamoghna Ghosh
Author Profile Icon Tamoghna Ghosh
Tamoghna Ghosh
Dipanjan Sarkar Dipanjan Sarkar
Author Profile Icon Dipanjan Sarkar
Dipanjan Sarkar
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Toc

Table of Contents (14) Chapters Close

Preface 1. Machine Learning Fundamentals FREE CHAPTER 2. Deep Learning Essentials 3. Understanding Deep Learning Architectures 4. Transfer Learning Fundamentals 5. Unleashing the Power of Transfer Learning 6. Image Recognition and Classification 7. Text Document Categorization 8. Audio Event Identification and Classification 9. DeepDream 10. Style Transfer 11. Automated Image Caption Generator 12. Image Colorization 13. Other Books You May Enjoy

Introduction

Before we dive in detail of neural DeepDream, let's take a glance at a similar behavior we humans experience ourselves. Have you ever tried to look for shapes in clouds, the jitter and noisy signals in your television set or even seen a face burned into your toast?

Pareidolia is a psychological phenomenon that leads us to see patterns in a random stimulus; the tendency for humans to perceive a face or pattern where one actually doesn't exist. This often results in assigning human characteristics to objects. Please note the significance of the evolutionary consequences of seeing a pattern where there is none (a false positive) as opposed to failing to see a pattern where there is one (a false negative). For example, seeing a lion where this is no lion is rarely lethal; however, failing to see a predatory lion where there is one, of course, would often be...

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