By Dipayan Dev
- Get to grips with the deep studying thoughts and manage Hadoop to place them to use
- Implement and parallelize deep studying versions on Hadoop's YARN framework
- A finished instructional to allotted deep studying with Hadoop
This e-book will educate you the way to install large-scale dataset in deep neural networks with Hadoop for optimum performance.
Starting with realizing what deep studying is, and what a number of the versions linked to deep neural networks are, this publication will then aid you manage the Hadoop atmosphere for deep studying. during this booklet, additionally, you will the best way to triumph over the demanding situations that you simply face whereas imposing allotted deep studying with large-scale unstructured datasets. The ebook also will express you the way you could enforce and parallelize the commonly used deep studying versions comparable to Deep trust Networks, Convolutional Neural Networks, Recurrent Neural Networks, constrained Boltzmann Machines and autoencoder utilizing the preferred deep studying library deeplearning4j.
Get in-depth mathematical factors and visible representations that can assist you comprehend the layout and implementations of Recurrent Neural community and Denoising AutoEncoders with deeplearning4j. to offer you a more effective standpoint, the ebook also will educate you the implementation of large-scale video processing, photo processing and traditional language processing on Hadoop.
By the top of this ebook, you are going to know the way to set up a variety of deep neural networks in dispensed platforms utilizing Hadoop.
What you'll learn
- Explore Deep studying and diverse versions linked to it
- Understand the demanding situations of imposing disbursed deep studying with Hadoop and the way to beat it
- Implement Convolutional Neural community (CNN) with deeplearning4j
- Delve into the implementation of constrained Boltzmann Machines (RBM)
- Understand the mathematical cause of imposing Recurrent Neural Networks (RNN)
- Get palms on perform of deep studying and their implementation with Hadoop.
About the Author
Dipayan Dev has accomplished his M.Tech from nationwide Institute of expertise, Silchar with a firstclass first and is at present operating as a software program specialist in Bengaluru, India. He has broad wisdom and event in non-relational database applied sciences, having basically labored with large-scale information over the past few years. His middle services lies in Hadoop Framework. in the course of his postgraduation, Dipayan had outfitted an unlimited scalable framework for Hadoop, referred to as Dr. Hadoop, which acquired released in top-tier SCI-E listed magazine of Springer (http://link.springer.com/article/10.1631/FITEE.1500015). Dr. Hadoop has lately been mentioned via Goo Wikipedia of their Apache Hadoop article. except that, he registers curiosity in a variety of allotted method applied sciences, corresponding to Redis, Apache Spark, Elasticsearch, Hive, Pig, Riak, and different NoSQL databases. Dipayan has additionally authored a variety of study papers and publication chapters, that are released via IEEE and top-tier Springer Journals. to understand extra approximately him, you may also stopover at his LinkedIn profile https://www.linkedin.com/in/dipayandev.
Table of Contents
- Introduction to Deep Learning
- Distributed Deep studying for Large-Scale Data
- Convolutional Neural Network
- Recurrent Neural Network
- Restricted Boltzmann Machines
- Miscellaneous Deep studying Operations utilizing Hadoop
Read or Download Deep Learning with Hadoop PDF
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Extra resources for Deep Learning with Hadoop
Deep Learning with Hadoop by Dipayan Dev