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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
Author Profile Icon Koki Saitoh
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

What Is a Perceptron?

A perceptron receives multiple signals as inputs and outputs one signal. The "signal" here "flows" like an electric current or a river. In the same way that an electric current flows through a conductor and pushes electrons forward, the signal in a perceptron makes flow and transfers information. Unlike an electric current, the signal in a perceptron is binary: "Flow (1) or Do not flow (0)." In this book, 0 indicates "do not flow a signal" and 1 indicates "flow a signal."

(In the interest of precision, note that the perceptron described in this chapter is more accurately called an "artificial neuron" or a "simple perceptron." Here, we will call it a "perceptron" because the basic processes are often the same.)

Figure 2.1 shows an example of a perceptron that receives two signals as input:

Figure 2.1: Perceptron with two inputs

x1 and x2 are input signals...

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