By Dipayan Dev
- Get to grips with the deep studying thoughts and arrange Hadoop to place them to use
- Implement and parallelize deep studying versions on Hadoop's YARN framework
- A complete instructional to allotted deep studying with Hadoop
This publication will train you ways to installation 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 types linked to deep neural networks are, this ebook will then make it easier to organize the Hadoop surroundings for deep studying. during this publication, additionally, you will the best way to conquer the demanding situations that you just face whereas enforcing dispensed deep studying with large-scale unstructured datasets. The publication also will convey you ways you could enforce and parallelize the commonly used deep studying versions corresponding to Deep trust Networks, Convolutional Neural Networks, Recurrent Neural Networks, limited Boltzmann Machines and autoencoder utilizing the preferred deep studying library deeplearning4j.
Get in-depth mathematical motives and visible representations that will help you comprehend the layout and implementations of Recurrent Neural community and Denoising AutoEncoders with deeplearning4j. to offer you a simpler standpoint, the booklet also will educate you the implementation of large-scale video processing, snapshot processing and traditional language processing on Hadoop.
By the top of this publication, you are going to understand how to set up a variety of deep neural networks in disbursed structures utilizing Hadoop.
What you are going to learn
- Explore Deep studying and diverse types 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 fingers 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 the moment operating as a software program specialist in Bengaluru, India. He has broad wisdom and adventure in non-relational database applied sciences, having basically labored with large-scale info over the past few years. His center services lies in Hadoop Framework. in the course of his postgraduation, Dipayan had outfitted an unlimited scalable framework for Hadoop, known 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 pointed out by way of Goo Wikipedia of their Apache Hadoop article. except that, he registers curiosity in a variety of dispensed method applied sciences, comparable to Redis, Apache Spark, Elasticsearch, Hive, Pig, Riak, and different NoSQL databases. Dipayan has additionally authored a variety of study papers and e-book chapters, that are released through IEEE and top-tier Springer Journals. to grasp extra approximately him, you can even 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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