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Deep Learning with Hadoop

You're reading from Deep Learning with Hadoop

Product type Book

Published in Feb 2017

Publisher Packt

ISBN-13 9781787124769

Pages 206 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Dipayan Dev

Table of Contents (16) Chapters

Deep Learning with Hadoop

Credits

About the Author

About the Reviewers

www.PacktPub.com

Customer Feedback

Dedication

Preface

1. Introduction to Deep Learning

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

Natural language processing using Hadoop

The exponential growth of information in the Web has increased the intensity of diffusion of large-scale unstructured natural language textual resources. Hence, in the last few years, the interest to extract, process, and share this information has increased substantially. Processing these sources of knowledge within a stipulated time frame has turned out to be a major challenge for various research and commercial industries. In this section, we will describe the process used to crawl the web documents, discover the information and run natural language processing in a distributed manner using Hadoop.

To design architecture for natural language processing (NLP), the first task to be performed is the extraction of annotated keywords and key phrases from the large-scale unstructured data. To perform the NLP on a distributed architecture, the Apache Hadoop framework can be chosen for its efficient and scalable solution, and also to improve the failure...

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Authors (1)

Dipayan Dev

Dipayan Dev has completed his M.Tech from National Institute of Technology, Silchar with a first class first and is currently working as a software professional in Bengaluru, India. He has extensive knowledge and experience in non-relational database technologies, having primarily worked with large-scale data over the last few years. His core expertise lies in Hadoop Framework. During his postgraduation, Dipayan had built an infinite scalable framework for Hadoop, called Dr. Hadoop, which got published in top-tier SCI-E indexed journal of Springer (http://link.springer.com/article/10.1631/FITEE.1500015). Dr. Hadoop has recently been cited by Goo Wikipedia in their Apache Hadoop article. Apart from that, he registers interest in a wide range of distributed system technologies, such as Redis, Apache Spark, Elasticsearch, Hive, Pig, Riak, and other NoSQL databases. Dipayan has also authored various research papers and book chapters, which are published by IEEE and top-tier Springer Journals. To know more about him, you can also visit his LinkedIn profile https://www.linkedin.com/in/dipayandev.

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