Deep Learning with Hadoop

Build, implement and scale distributed deep learning models for large-scale datasets

Key Features

• Get to grips with the deep learning concepts and set up Hadoop to put them to use
• Implement and parallelize deep learning models on Hadoop’s YARN framework
• A comprehensive tutorial to distributed deep learning with Hadoop

Book Description

What you will learn

• Explore Deep Learning and various models associated with it
• Understand the challenges of implementing distributed deep learning with Hadoop and how to overcome it
• Implement Convolutional Neural Network (CNN) with Deeplearning4j
• Delve into the implementation of Restricted Boltzmann machines (RBMs)
• Understand the mathematical explanation for implementing Recurrent Neural Networks (RNNs)
• Understand the design and implementation of Deep Belief Networks (DBN) and Deep Autoencoders using Deeplearning4j
• Get hands on practice of deep learning and their implementation with Hadoop.

Who this book is for

If you are a data scientist who wants to learn how to perform deep learning on Hadoop, this is the book for you. Knowledge of the basic machine learning concepts and some understanding of Hadoop is required to make the best use of this book.