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Deep Learning with Hadoop. Distributed Deep Learning with Large-Scale Data Dipayan Dev

(ebook) (audiobook) (audiobook) Książka w języku 1
Deep Learning with Hadoop. Distributed Deep Learning with Large-Scale Data Dipayan Dev - okladka książki

Deep Learning with Hadoop. Distributed Deep Learning with Large-Scale Data Dipayan Dev - okladka książki

Deep Learning with Hadoop. Distributed Deep Learning with Large-Scale Data Dipayan Dev - audiobook MP3

Deep Learning with Hadoop. Distributed Deep Learning with Large-Scale Data Dipayan Dev - audiobook CD

Autor:
Dipayan Dev
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
206
Dostępne formaty:
     PDF
     ePub
     Mobi
This book will teach you how to deploy
large-scale dataset in deep neural networks with Hadoop for
optimal performance.

Starting with understanding what deep
learning is, and what the various models
associated with deep neural networks are, this
book will then show you how to set up the
Hadoop environment for deep learning.
In this book, you will also learn how to
overcome the challenges that you face
while implementing distributed deep
learning with large-scale unstructured datasets. The book will
also show you how you can implement
and parallelize the widely used deep learning models such as Deep Belief Networks,
Convolutional Neural Networks, Recurrent Neural Networks, Restricted Boltzmann machines and autoencoder using the popular deep learning library Deeplearning4j.

Get in-depth mathematical explanations
and visual representations to help
you understand the design and implementations
of Recurrent Neural network and Denoising Autoencoders with
Deeplearning4j. To give you a more
practical perspective, the book will also
teach you the implementation of large-scale video processing, image processing and
natural language processing on Hadoop.

By the end of this book, you will
know how to deploy various deep neural networks in
distributed systems using Hadoop.

Wybrane bestsellery

O autorze książki

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 (https://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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