Lantz - Machine Learning with R

Brett Lantz has spent more than 10 years using innovative data methods to understand human behavior. A trained sociologist, he was first enchanted by machine learning while studying a large database of teenagers' social networking website profiles. Since then, Brett has worked on interdisciplinary studies of cellular telephone calls, medical billing data, and philanthropic activity, among others. When not spending time with family, following college sports, or being entertained by his dachshunds, he maintains http://dataspelunking.com/, a website dedicated to sharing knowledge about the search for insight in data.

This book could not have been written without the support of my friends and family. In particular, my wife, Jessica, deserves many thanks for her endless patience and encouragement. My son, Will, who was born in the midst of the first edition and supplied much-needed diversions while writing this edition, will be a big brother shortly after this book is published. In spite of cautionary tales about correlation and causation, it seems that every time I expand my written library, my family likewise expands! I dedicate this book to my children in the hope that one day they will be inspired to tackle big challenges and follow their curiosity wherever it may lead.

I am also indebted to many others who supported this book indirectly. My interactions with educators, peers, and collaborators at the University of Michigan, the University of Notre Dame, and the University of Central Florida seeded many of the ideas I attempted to express in the text; any lack of clarity in their expression is purely mine. Additionally, without the work of the broader community of researchers who shared their expertise in publications, lectures, and source code, this book might not have existed at all. Finally, I appreciate the efforts of the R team and all those who have contributed to R packages, whose work has helped bring machine learning to the masses. I sincerely hope that my work is likewise a valuable piece in this mosaic.

Vijayakumar Nattamai Jawaharlal is a software engineer with an experience of 2 decades in the IT industry. His background lies in machine learning, big data technologies, business intelligence, and data warehouse.

He develops scalable solutions for many distributed platforms, and is very passionate about scalable distributed machine learning.

Kent S. Johnson is a software developer who loves data analysis, statistics, and machine learning. He currently develops software to analyze tissue samples related to cancer research. According to him, a day spent with R and ggplot2 is a good day. For more information about him, visit http://kentsjohnson.com.

I'd like to thank, Gile, for always loving me.

Mzabalazo Z. Ngwenya holds a postgraduate degree in mathematical statistics from the University of Cape Town. He has worked extensively in the field of statistical consulting, and currently works as a biometrician at a research and development entity in South Africa. His areas of interest are primarily centered around statistical computing, and he has over 10 years of experience with R for data analysis and statistical research. Previously, he was involved in reviewing Learning RStudio for R Statistical Computing , R Statistical Application Development by Example Beginner's Guide , R Graph Essentials , R Object-oriented Programming , Mastering Scientific Computing with R , and Machine Learning with R , all by Packt Publishing.

Anuj Saxena is a data scientist at IGATE Corporation. He has an MS in analytics from the University of San Francisco and an MSc in Statistics from the NMIMS University in India. He is passionate about data science and likes using open source languages such as R and Python as primary tools for data science projects. In his spare time, he participates in predictive analytics competitions on kaggle.com. For more information about him, visit http://www.anuj-saxena.com.

I'd like to thank my father, Dr. Sharad Kumar, who inspired me at an early age to learn math and statistics and my mother, Mrs. Ranjana Saxena, who has been a backbone throughout my educational life.

I'd also like to thank my wonderful professors at the University of San Francisco and the NMIMS University who triggered my interest in this field and taught me the power of data and how it can be used to tell a wonderful story.