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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

A Brief History of Deep Learning

It is said that deep learning started to draw a lot of attention in the competition of large-scale image recognition due to the ImageNet Large Scale Visual Recognition Challenge (ILSRVC), which was held in 2012. In the competition, a deep learning technique called AlexNet achieved an overwhelming win, overturning the traditional approaches to image recognition. Since deep learning launched a counterattack in 2012, it has always played the leading role in subsequent competitions. Here, we will look at the current trend of deep learning around the competition of large-scale image recognition, known as ILSVRC.

ImageNet

ImageNet (J. Deng, W. Dong, R. Socher, L.J. Li, Kai Li, and Li Fei-Fei (2009): ImageNet: A large-scale hierarchical image database. In IEEE Conference on Computer Vision and Pattern Recognition, 2009. CVPR 2009. 248 – 255. DOI: (http://dx.doi.org/10.1109/CVPR.2009.5206848)) is a dataset that contains more than 1 million images...

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