Aloysius Lim - R High Performance Programming

Aloysius Lim has a knack for translating complex data and models into easy-to-understand insights. As cofounder of About People, a data science and design consultancy, he loves solving problems and helping others to find practical solutions to business challenges using data. His breadth of experience7 years in the government, education, and retail industriesequips him with unique perspectives to find creative solutions.

My deepest thanks go to God for the opportunity to write this book and share the knowledge that I have been given. My lovely wife, Bethany, has been a tremendous source of support and encouragement throughout this project. Thank you dear, for all your love. Many thanks to my partner William for his wonderful friendship. He has been a source of inspiration and insights throughout this journey.

William Tjhi is a data scientist with years of experience working in academia, government, and industry. He began his data science journey as a PhD candidate researching new algorithms to improve the robustness of high-dimensional data clustering. Upon receiving his doctorate, he moved from basic to applied research, solving problems among others in molecular biology and epidemiology using machine learning. He published some of his research in peer-reviewed journals and conferences. With the rise of Big Data, William left academia for industry, where he started practicing data science in both business and public sector settings. William is passionate about R and has been using it as his primary analysis tool since his research days. He was once part of Revolution Analytics, and there he contributed to make R more suitable for Big Data.

I would like to thank my coauthor, Aloysius. Your hard work, patience, and determination made this book possible.

Richard Cotton is a data scientist with a mixed background in proteomics, debt collection, and chemical health and safety, and he has worked extensively on tools to give nontechnical users access to statistical models. He is the author of the book Learning R , O'Reilly , and has created a number of popular R packages, including assertive, regex, pathological, and sig. He works for Weill Cornell Medical College in Qatar.

Kirill Mller holds a diploma in computer science and currently works as a research assistant at the Institute for Transport Planning and Systems of the Swiss Federal Institute of Technology (ETHZ) in Zurich. He is an avid R user and has contributed to several R packages.

John Silberholz is a fourth year PhD student at the MIT Operations Research Center, working under advisor Dimitris Bertsimas. His thesis research focuses on data-driven approaches to design novel chemotherapy regimens for advanced cancer and approaches to identify effective population screening strategies for cancer. His research interests also include analytical applications in the fields of bibliometrics and heuristic evaluation. John codeveloped 15.071x: The Analytics Edge , a massive open online course (MOOC), which teaches machine learning and optimization using R and spreadsheet solvers.

Before coming to MIT, John completed his BS degree in mathematics and computer science from the University of Maryland. He completed internships as a software developer at Microsoft and Google, and he cofounded Enertaq, an electricity grid reliability start-up.

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Preface

In a world where data is becoming increasingly important, business people and scientists need tools to analyze and process large volumes of data efficiently. R is one of the tools that have become increasingly popular in recent years for data processing, statistical analysis, and data science. While R has its roots in academia, it is now used by organizations across a wide range of industries and geographical areas.

But the design of R imposes some inherent limits on the size of the data and the complexity of computations that it can manage efficiently. This can be a huge obstacle for R users who need to process the ever-growing volume of data in their organizations.