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
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
Index

Understanding machine learning


Aren't we taught that computer systems have to be programmed to do certain tasks? They may be a million times faster at doing things but they have to be programmed. We have to code each and every step and only then do these systems work and complete a task. Isn't then the very notion of machine learning a very contradictory concept?

In the simplest ways, machine learning refers to a method of teaching the systems to learn to do certain tasks, such as learning a function. As simple as it sounds, it is a bit confusing and difficult to digest. Confusing because our view of the way the systems (computer systems specifically) work and the way we learn are two concepts that hardly intersect. It is even more difficult to digest because learning, though an inherent capability of the human race, is difficult to put in to words, let alone teach to the systems.

Then what is machine learning? Before we even try to answer this question, we need to understand that at a philosophical...