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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

Multilayer Perceptrons

Unfortunately, we cannot use a perceptron to represent an XOR gate. However, this is not terrible news. Actually, the merit of a perceptron lies in the fact that multiple layers of perceptrons can be stacked (the outline of this section is that multiple layers can represent XOR). We will look at the stacking layers later. Here, we can consider the problem of the XOR gate from another viewpoint.

Combining the Existing Gates

There are some methods we can follow to make an XOR gate. One of them is to combine the AND, NAND, and OR gates that we have created so far and wire them. Here, the AND, NAND, and OR gates are shown with symbols in Figure 2.9. The circle at the tip of the NAND gate in Figure 2.9 indicates that an output has been reversed.

Figure 2.9: Symbols of the AND, NAND, and OR gates

Now, let's think about how we can wire AND, NAND, and OR to create an XOR gate. Note that you can assign AND, NAND, or OR to each of the...

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