By Dipayan Dev
- Get to grips with the deep studying techniques and organize Hadoop to place them to use
- Implement and parallelize deep studying types on Hadoop's YARN framework
- A accomplished educational to allotted deep studying with Hadoop
This booklet will train you ways to install large-scale dataset in deep neural networks with Hadoop for optimum performance.
Starting with figuring out what deep studying is, and what a few of the versions linked to deep neural networks are, this booklet will then enable you to arrange the Hadoop atmosphere for deep studying. during this publication, additionally, you will conquer the demanding situations that you just face whereas enforcing disbursed deep studying with large-scale unstructured datasets. The publication also will convey you the way you could enforce and parallelize the generally used deep studying types akin 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 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 publication also will train you the implementation of large-scale video processing, snapshot processing and normal language processing on Hadoop.
By the top of this booklet, you are going to know the way to set up quite a few deep neural networks in dispensed platforms utilizing Hadoop.
What you are going to learn
- Explore Deep studying and numerous versions linked to it
- Understand the demanding situations of enforcing dispensed deep studying with Hadoop and the way to beat it
- Implement Convolutional Neural community (CNN) with deeplearning4j
- Delve into the implementation of limited 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 present 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 information over the past few years. His middle services lies in Hadoop Framework. in the course of his postgraduation, Dipayan had equipped an enormous 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 brought up through Goo Wikipedia of their Apache Hadoop article. except that, he registers curiosity in a variety of disbursed method applied sciences, comparable to Redis, Apache Spark, Elasticsearch, Hive, Pig, Riak, and different NoSQL databases. Dipayan has additionally authored numerous examine papers and booklet chapters, that are released via IEEE and top-tier Springer Journals. to grasp 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
Similar data modeling & design books
Learn how to remedy medical computing difficulties utilizing Scala and its numerical computing, facts processing, concurrency, and plotting librariesAbout This BookParallelize your numerical computing code utilizing handy and secure recommendations. Accomplish universal high-performance, clinical computing pursuits in Scala.
Solid Programming in SAP BW utilizing ABAP is my own view on tips on how to organize coding for handling thousands of files within the so much performant demeanour. might be, you may be stunned that there are usually not 500 pages dedicated to the secrets and techniques of performant ABAP coding yet that i've got coated the details of curiosity in below 50 published pages.
Key FeaturesPredict and use a probabilistic graphical types (PGM) as a professional systemComprehend how your laptop can study Bayesian modeling to resolve real-world problemsKnow tips to arrange information and feed the versions by utilizing the precise algorithms from the correct R packageBook DescriptionProbabilistic graphical types (PGM, often referred to as graphical versions) are a wedding among chance conception and graph idea.
Functions of huge facts, information research, and information administration within the improvement of schooling software program
- Contextual Design: Evolved
- Knowledge and Data Management in GRIDs
- Visualizing Data: Exploring and Explaining Data with the Processing Environment
- Data Model Patterns: A Metadata Map (The Morgan Kaufmann Series in Data Management Systems)
- Apache Spark 2.x Cookbook
Extra info for Deep Learning with Hadoop
Deep Learning with Hadoop by Dipayan Dev