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)

Introduction to Machine Learning with Scala

In this chapter, we will explain some basic concepts of machine learning (ML) that will be used in all subsequent chapters. We will start with a brief introduction to ML including basic learning workflow, ML rule of thumb, and different learning tasks. Then we will gradually cover most important ML tasks.

Also, we will discuss getting started with Scala and Scala-based ML libraries for getting a quick start for the next chapter. Finally, we get started with ML with Scala and Spark ML by solving a real-life problem. The chapter will briefly cover the following topics:

  • Overview of ML
  • ML tasks
  • Introduction to Scala
  • Scala ML libraries
  • Getting started with ML with Spark ML