Book Image

Machine Learning with Scala Quick Start Guide

By : Md. Rezaul Karim, Ajay Kumar N
Book Image

Machine Learning with Scala Quick Start Guide

By: Md. Rezaul Karim, Ajay Kumar N

Overview of this book

Scala is a highly scalable integration of object-oriented nature and functional programming concepts that make it easy to build scalable and complex big data applications. This book is a handy guide for machine learning developers and data scientists who want to develop and train effective machine learning models in Scala. The book starts with an introduction to machine learning, while covering deep learning and machine learning basics. It then explains how to use Scala-based ML libraries to solve classification and regression problems using linear regression, generalized linear regression, logistic regression, support vector machine, and Naïve Bayes algorithms. It also covers tree-based ensemble techniques for solving both classification and regression problems. Moving ahead, it covers unsupervised learning techniques, such as dimensionality reduction, clustering, and recommender systems. Finally, it provides a brief overview of deep learning using a real-life example in Scala.
Table of Contents (9 chapters)

Overview of Scala

Scala is a scalable, functional, and object-oriented programming language that is most closely related to Java. However, Scala is designed to be more concise and have features of functional programming languages. For example, Apache Spark, which is written in Scala, is a fast and general engine for large-scale data processing.

Scala's success is due to many factors: it has many tools that enable succinct expression, it is very concise because you need less typing, and it therefore requires less reading, and it offers very good performance as well. This is why Spark has more support for Scala in the sense that more APIs are available that are written in Scala compared to R, Python, and Java. Scala's symbolic operators are easy to read and, compared to Java, most of the Scala codes are comparatively concise and easy to read; Java is too verbose. Functional programming concepts such as pattern matching and higher-order functions are also available in Scala.

The best way to get started with Scala is either using Scala through the Scala build tool (SBT) or to use Scala through an integrated development environment (IDE). Either way, the first important step is downloading, installing, and configuring Scala. However, since Scala runs on Java Virtual Machine (JVM), having Java installed and configured on your machine is a prerequisite. Therefore, I'm not going to cover how to do that. Instead, I will provide some useful links (

Just follow the instructions on how to set up both Java and an IDE (for example, IntelliJ IDEA) or build tool (for example, SBT) at If you're using Windows (for example, Windows 10) or Linux (for example, Ubuntu), visit Finally, here are some macOS instructions:

Java programmers normally prefer Scala when they need to add some functional programming flavor to their codes as Scala runs on JVM. There are various other options when it comes to editors. The following are some options to choose from:

  • Scala IDE
  • Scala plugin for Eclipse
  • IntelliJ IDEA
  • Emacs
  • Vim

Eclipse has several advantages using numerous beta plugins and local, remote, and high-level debugging facilities with semantic highlighting and code completion for Scala.