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 Deep Learning with Scala

Throughout Chapter 2, Scala for Regression Analysis, to Chapter 6, Scala for Recommender System, we have learned about linear and classic machine learning (ML) algorithms through real-life examples. In this chapter, we will explain some basic concepts of deep learning (DL). We will start with DL, which is one of the emerging branches of ML. We will briefly discuss some of the most well-known and widely used neural network architectures and DL frameworks and libraries.

Finally, we will use the Long Short-Term Memory (LSTM) architecture for cancer type classification from a very high-dimensional dataset curated from The Cancer Genome Atlas (TCGA). The following topics will be covered in this chapter:

  • DL versus ML
  • DL and neural networks
  • Deep neural network architectures
  • DL frameworks
  • Getting started with learning