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Deep Learning with Hadoop

You're reading from   Deep Learning with Hadoop Distributed Deep Learning with Large-Scale Data

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Product type Paperback
Published in Feb 2017
Publisher Packt
ISBN-13 9781787124769
Length 206 pages
Edition 1st Edition
Languages
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Author (1):
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Dipayan Dev Dipayan Dev
Author Profile Icon Dipayan Dev
Dipayan Dev
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Table of Contents (9) Chapters Close

Preface 1. Introduction to Deep Learning 2. Distributed Deep Learning for Large-Scale Data FREE CHAPTER 3. Convolutional Neural Network 4. Recurrent Neural Network 5. Restricted Boltzmann Machines 6. Autoencoders 7. Miscellaneous Deep Learning Operations using Hadoop 1. References

Chapter 3.  Convolutional Neural Network

 

"The question of whether a computer can think is no more interesting than the question of whether a submarine can swim."

 
 --Edsger W. Dijkstra

Convolutional neural network (CNN)--doesn't it give an uncanny feeling about the combination of mathematics and biology with some negligible amount of computer science added? However, these type of networks have been some of the most dominant and powerful architectures in the field of computer vision. CNN started to gain its popularity after 2012, when there were huge improvements in the precision of classification, credit to some pioneer in the field of deep learning. Ever since then, a bunch of high-tech companies have been using deep CNN for various services. Amazon uses CNN for their product recommendations, Google uses it for their photo search, and Facebook primarily uses it for its automatic tagging algorithms.

CNN [89] is a type of feed-forward neural...

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