Fischetti - Data Analysis with R

Tony Fischetti is a data scientist at College Factual, where he gets to use R everyday to build personalized rankings and recommender systems. He graduated in cognitive science from Rensselaer Polytechnic Institute, and his thesis was strongly focused on using statistics to study visual short-term memory.

Tony enjoys writing and contributing to open source software, blogging at http://www.onthelambda.com, writing about himself in third person, and sharing his knowledge using simple, approachable language and engaging examples.

The more traditionally exciting of his daily activities include listening to records, playing the guitar and bass (poorly), weight training, and helping others.

Because I'm aware of how incredibly lucky I am, it's really hard to express all the gratitude I have for everyone in my life that helped meeither directly, or indirectlyin completing this book. The following (partial) list is my best attempt at balancing thoroughness whilst also maximizing the number of people who will read this section by keeping it to a manageable length.

First, I'd like to thank all of my educators. In particular, I'd like to thank the Bronx High School of Science and Rensselaer Polytechnic Institute. More specifically, I'd like the Bronx Science Robotics Team, all it's members, it's team moms, the wonderful Dena Ford and Cherrie Fleisher-Strauss; and Justin Fox. From the latter institution, I'd like to thank all of my professors and advisors. Shout out to Mike Kalsher, Michael Schoelles, Wayne Gray, Bram van Heuveln, Larry Reid, and Keith Anderson (especially Keith Anderson).

I'd like to thank the New York Public Library, Wikipedia, and other freely available educational resources. On a related note, I need to thank the R community and, more generally, all of the authors of R packages and other open source software I use for spending their own personal time to benefit humanity. Shout out to GNU, the R core team, and Hadley Wickham (who wrote a majority of the R packages I use daily).

Next, I'd like to thank the company I work for, College Factual, and all of my brilliant co-workers from whom I've learned so much.

I also need to thank my support network of millions, and my many many friends that have all helped me more than they will likely ever realize.

I'd like to thank my partner, Bethany Wickham, who has been absolutely instrumental in providing much needed and appreciated emotional support during the writing of this book, and putting up with the mood swings that come along with working all day and writing all night.

Next, I'd like to express my gratitude for my sister, Andrea Fischetti, who means the world to me. Throughout my life, she's kept me warm and human in spite of the scientist in me that likes to get all reductionist and cerebral.

Finally, and most importantly, I'd like to thank my parents. This book is for my father, to whom I owe my love of learning and my interest in science and statistics; and to my mother for her love and unwavering support and, to whom I owe my work ethic and ability to handle anything and tackle any challenge.

Dipanjan Sarkar is an IT engineer at Intel, the world's largest silicon company, where he works on analytics, business intelligence, and application development. He received his master's degree in information technology from the International Institute of Information Technology, Bangalore. Dipanjan's area of specialization includes software engineering, data science, machine learning, and text analytics.

His interests include learning about new technologies, disruptive start-ups, and data science. In his spare time, he loves reading, playing games, and watching popular sitcoms. Dipanjan also reviewed Learning R for Geospatial Analysis and R Data Analysis Cookbook , both by Packt Publishing.

I would like to thank Bijal Patel, the project coordinator of this book, for making the reviewing experience really interactive and enjoyable.