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Deep Learning from the Basics

You're reading from   Deep Learning from the Basics Python and Deep Learning: Theory and Implementation

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Product type Paperback
Published in Mar 2021
Publisher Packt
ISBN-13 9781800206137
Length 316 pages
Edition 1st Edition
Languages
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Authors (2):
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Shigeo Yushita Shigeo Yushita
Author Profile Icon Shigeo Yushita
Shigeo Yushita
Koki Saitoh Koki Saitoh
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Koki Saitoh
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Toc

Table of Contents (11) Chapters Close

Preface Introduction 1. Introduction to Python FREE CHAPTER 2. Perceptrons 3. Neural Networks 4. Neural Network Training 5. Backpropagation 6. Training Techniques 7. Convolutional Neural Networks 8. Deep Learning Appendix A

Loss Function

How do you answer when you are asked, "How happy are you now?". We may usually answer vaguely: "I am moderately happy" or "I am not very happy." You may be surprised if someone answers, "My current happiness score is 10.23" because the person can only quantify their happiness with one score. If such a person exists, the person may lead their life only based on their "happiness score."

This "happiness score" is an allegory used to illustrate some similar things which occur in neural network training. In neural network training, one "score" is used to indicate the current status. Based on the score, optimal weight parameters are searched for. As this person looks for an "optimal life" based on the "happiness score," a neural network searches for optimal parameters using "one score" as a guide. The score that's used in neural network training is called a loss function...

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