Running a feed-forward neural network with DeepLearning 4j over Spark

DeepLearning4j (DL4J) is an open source deep learning library written in Java and Scala and which is used in business environments. This can be easily integrated with GPU and scaled on Hadoop or Spark. It supports a stack of neural networks for image recognition, text analysis and speech to text. Hence, it has implementations for algorithms such as binary and continuous restricted Boltzmann machines, deep belief networks, de-noising auto-encoders, convolutional networks and recursive neural tensor networks.

Getting ready

To step through this recipe, you will need a running Spark cluster either in pseudo distributed mode or in one of the distributed modes, that is, standalone, YARN, or Mesos. Also, get familiar with ND4S, that is, n-dimensional arrays for Scala (Scala bindings for ND4J). ND4J and ND4S are scientific computing libraries for the JVM. Please visit http://nd4j.org/ for details. The pre-requisites to be installed...