Book Image

R Machine Learning By Example

By : Raghav Bali
Book Image

R Machine Learning By Example

By: Raghav Bali

Overview of this book

Data science and machine learning are some of the top buzzwords in the technical world today. From retail stores to Fortune 500 companies, everyone is working hard to making machine learning give them data-driven insights to grow their business. With powerful data manipulation features, machine learning packages, and an active developer community, R empowers users to build sophisticated machine learning systems to solve real-world data problems. This book takes you on a data-driven journey that starts with the very basics of R and machine learning and gradually builds upon the concepts to work on projects that tackle real-world problems. You’ll begin by getting an understanding of the core concepts and definitions required to appreciate machine learning algorithms and concepts. Building upon the basics, you will then work on three different projects to apply the concepts of machine learning, following current trends and cover major algorithms as well as popular R packages in detail. These projects have been neatly divided into six different chapters covering the worlds of e-commerce, finance, and social-media, which are at the very core of this data-driven revolution. Each of the projects will help you to understand, explore, visualize, and derive insights depending upon the domain and algorithms. Through this book, you will learn to apply the concepts of machine learning to deal with data-related problems and solve them using the powerful yet simple language, R.
Table of Contents (15 chapters)
R Machine Learning By Example
About the Authors
About the Reviewer

Algorithms in machine learning

So far we have developed an abstract understanding of machine learning. We understand the definition of machine learning which states that a task T can be learned by a computer program utilizing data in the form of experience E when its performance P improves with it. We have also seen how machine learning is different from conventional programming paradigms because of the fact that we do not code each and every step, rather we let the program form an understanding of the problem space and help us solve it. It is rather surprising to see such a program work right in front of us.

All along while we learned about the concept of machine learning, we treated this magical computer program as a mysterious black box which learns and solves the problems for us. Now is the time we unravel its enigma and look under the hood and see these magical algorithms in full glory.

We will begin with some of the most commonly and widely used algorithms in machine learning, looking...