Contributors

About the authors

Brett Lantz (@DataSpelunking) has spent more than 10 years using innovative data methods to understand human behavior. A sociologist by training, Brett was first captivated by machine learning during research on a large database of teenagers' social network profiles. Brett is a DataCamp instructor and a frequent speaker at machine learning conferences and workshops around the world. He is known to geek out about data science applications for sports, autonomous vehicles, foreign language learning, and fashion, among many other subjects, and hopes to one day blog about these subjects at 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 family. In particular, my wife Jessica deserves many thanks for her endless patience and encouragement. My sons Will and Cal were born in the midst of the first and second editions, respectively, and supplied much-needed diversions while writing this edition. I dedicate this book to them in the hope that one day they are 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 exist at all. Finally, I appreciate the efforts of the R and RStudio teams and all those who have contributed to R packages, whose work have helped bring machine learning to the masses. I sincerely hope that my work is likewise a valuable piece in this mosaic.

About the reviewer

Raghav Bali is a Senior Data Scientist at one of the world's largest healthcare organization. His work involves research and development of enterprise level solutions based on machine learning, deep learning and natural language processing for healthcare and insurance related use cases. In his previous role at Intel, he was involved in enabling proactive data driven IT initiatives using natural language processing, deep learning and traditional statistical methods. He has also worked in finance domain with American Express, solving digital engagement and customer retention use cases.

Raghav has also authored multiple books with leading publishers, the recent one on latest advancements in transfer learning research.

Raghav has a master's degree (gold medalist) in Information Technology from International Institute of Information Technology, Bangalore. Raghav loves reading and is a shutterbug capturing moments when he isn't busy solving problems.