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Apache Spark for Data Science Cookbook

You're reading from Apache Spark for Data Science Cookbook Solve real-world analytical problems

Product type Paperback

Published in Dec 2016

Publisher

ISBN-13 9781785880100

Length 392 pages

Edition 1st Edition

Tools

Apache Spark

Concepts

Data Science

Authors (2):

Padma Priya Chitturi

Nagamallikarjuna Inelu

View More author details

Table of Contents (11) Chapters

Preface

1. Big Data Analytics with Spark

2. Tricky Statistics with Spark FREE CHAPTER

3. Data Analysis with Spark

4. Clustering, Classification, and Regression

5. Working with Spark MLlib

6. NLP with Spark

7. Working with Sparkling Water - H2O

8. Data Visualization with Spark

9. Deep Learning on Spark

10. Working with SparkR

Running an RBM with DeepLearning4j over Spark

In this recipe, we'll see how to run a restricted Boltzmann machine for classifying the iris dataset.

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 are Java 7, IntelliJ, and the Maven or SBT build tool.

How to do it…

Start an application named RBMWithSpark. Initially, specify the following libraries in the build.sbt file:

      libraryDependencies ++= Seq( 
      "org.apache.spark" %% "spark-core" % "1.6.0", 
      "org.apache.spark" %% "spark-mllib" % "1.6.0", 
      "org.deeplearning4j" % &quot...

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Authors (2)

Chitturi

Chitturi

Padma Priya Chitturi is Analytics Lead at Fractal Analytics Pvt Ltd and has over five years of experience in Big Data processing. Currently, she is part of capability development at Fractal and responsible for solution development for analytical problems across multiple business domains at large scale. Prior to this, she worked for an Airlines product on a real-time processing platform serving one million user requests/sec at Amadeus Software Labs. She has worked on realizing large-scale deep networks (Jeffrey deans work in Google brain) for image classification on the big data platform Spark. She works closely with Big Data technologies such as Spark, Storm, Cassandra and Hadoop. She was an open source contributor to Apache Storm.

See other products by Chitturi

Nagamallikarjuna Inelu

Nagamallikarjuna Inelu

See other products by Nagamallikarjuna Inelu

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