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  • This chapter is unavailable for purchase
  • Print publication year: 2019
  • Online publication date: April 2019

Preface

Summary

In the modern age of artificial intelligence and business analytics, data is considered as the oil of this cyber world. The mining of data has huge potential to improve business outcomes, and to carry out the mining of data there is a growing demand for database mining experts. This book intends training learners to fill this gap.

This book will give learners sufficient information to acquire mastery over the subject. It covers the practical aspects of data mining, data warehousing, and machine learning in a simplified manner without compromising on the details of the subject. The main strength of the book is the illustration of concepts with practical examples so that the learners can grasp the contents easily. Another important feature of the book is illustration of data mining algorithms with practical hands-on sessions on Weka and R language (a major data mining tool and language, respectively). In this book, every concept has been illustrated through a step-by-step approach in tutorial form for self-practice in Weka and R. This textbook includes many pedagogical features such as chapter wise summary, exercises including probable problems, question bank, and relevant references, to provide sound knowledge to learners. It provides the students a platform to obtain expertise on technology, for better placements.

Video sessions on data mining, machine learning, big data and DBMS are also available on my YouTube channel. Learners are requested to subscribe to this channel https://www.youtube.com/user/parteekbhatia to get the latest updates through video sessions on these topics.

Your suggestions for further improvements to the book are always welcome. Kindly e-mail your suggestions to parteek.bhatia@gmail.com.

I hope you enjoy learning from this book as much as I enjoyed writing it.