Deep learning with Hadoop : build, implement and scale distributed deep learning models for large-scale datasets.

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Book Description

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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.

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Table of Contents

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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