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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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Toc

Table of Contents (9) Chapters Close

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

What you need for this book

We expect all the readers of this book to have some background on computer science. This book mainly talks on different deep neural networks, their designs and applications with Deeplearning4j. To extract the most out of the book, the readers are expected to know the basics of machine learning, linear algebra, probability theory, the concepts of distributed systems and Hadoop. For the implementation of deep neural networks with Hadoop, Deeplearning4j has been extensively used throughout this book. Following is the link for everything you need to run Deeplearning4j:

https://deeplearning4j.org/quickstart

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