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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

Summary


This chapter discussed the most widely used applications of Machine learning and how they can be designed in the Hadoop framework. First, we started with a large video set and showed how the video can be decoded in the HDFS and later converted into a sequence file containing images for later processing. Large-scale image processing was discussed next in the chapter. The mapper used for this purpose has a shell script which performs all the tasks necessary. So, no reducer is necessary to perform this operation. Finally, we discussed how the natural language processing model can be deployed in Hadoop.

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