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Mastering Scala Machine Learning

Mastering Scala Machine Learning

By : Kozlov
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Mastering Scala Machine Learning

Mastering Scala Machine Learning

By: Kozlov

Overview of this book

Since the advent of object-oriented programming, new technologies related to Big Data are constantly popping up on the market. One such technology is Scala, which is considered to be a successor to Java in the area of Big Data by many, like Java was to C/C++ in the area of distributed programing. This book aims to take your knowledge to next level and help you impart that knowledge to build advanced applications such as social media mining, intelligent news portals, and more. After a quick refresher on functional programming concepts using REPL, you will see some practical examples of setting up the development environment and tinkering with data. We will then explore working with Spark and MLlib using k-means and decision trees. Most of the data that we produce today is unstructured and raw, and you will learn to tackle this type of data with advanced topics such as regression, classification, integration, and working with graph algorithms. Finally, you will discover at how to use Scala to perform complex concept analysis, to monitor model performance, and to build a model repository. By the end of this book, you will have gained expertise in performing Scala machine learning and will be able to build complex machine learning projects using Scala.
Table of Contents (12 chapters)
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10
10. Advanced Model Monitoring
11
Index

What you need for this book

This book is based on open source software. First, it's Java. One can download Java from Oracle's Java Download page. You have to accept the license and choose an appropriate image for your platform. Don't use OpenJDK—it has a few problems with Hadoop/Spark.

Second, Scala. If you are using Mac, I recommend installing Homebrew:

$ ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"

Multiple open source packages will also be available to you. To install Scala, run brew install scala. Installation on a Linux platform requires downloading an appropriate Debian or RPM package from the http://www.scala-lang.org/download/ site. We will use the latest version at the time, that is, 2.11.7.

Spark distributions can be downloaded from http://spark.apache.org/downloads.html. We use pre-build for Hadoop 2.6 and later image. As it's Java, you need to just unzip the package and start using the scripts from the bin subdirectory.

R and Python packages are available at http://cran.r-project.org/bin and http://python.org/ftp/python/$PYTHON_VERSION/Python-$PYTHON_VERSION.tar.xz sites respectively. The text has specific instruction on how to configure them. Although our use of the packages should be version agnostic, I used R version 3.2.3 and Python version 2.7.11 in this book.

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Mastering Scala Machine Learning
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