Roger D. Peng
Department of Biostatistics
Johns Hopkins Bloomberg School of Public Health
615 N. Wolfe St.
Baltimore, MD 21205
Office: E3535
Phone: (410) 955-2468
Fax: (410) 955-0958
Email: rpeng at jhsph.edu
URL: http://www.biostat.jhsph.edu/~rpeng/
Education
Postdoctoral Fellow, Biostatistics, Johns Hopkins Bloomberg School of Public Health, 2003–2005
Ph.D. Statistics, University of California, Los Angeles, 2003
M.S. Statistics, University of California, Los Angeles, 2001
B.S. Applied Mathematics, Yale University, 1999
Experience
Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health
Professor, 2016–present
Associate Professor, 2010–2016
Assistant Professor, 2005–2010
Director, Training Program in Environmental Biostatistics, 2012–2015
Co-Director, Data Management and Statistics Core, Johns Hopkins Children's Center for Asthma in the Urban Environment, 2010–present
Director, Data Management Core, Johns Hopkins Particulate Matter Research Center, 2008–2010
Department of Statistics, UCLA
Graduate Student Researcher, 2000–2003
Logicon INRI/Northrop Grumman
Software Engineer — UnderSea Warfare Systems and Cartography, 1998 (summer)
KenCast, Inc.
Software Engineer, 1997, 1999 (summer)
Honors and Awards
APHA Mortimer Spiegelman Award, 2016
NIH R21: Extreme heat and health: Characterizing vulnerability in a changing climate (2011–2013)
NIH R01: Statistical methods for complex environmental health data (2011–2015)
Lead author of NIEHS Extramural Paper of the Month, July 2008
Second author of NIEHS Extramural Paper of the Month, December 2007
Lead author of #1 most cited paper in the Journal of the Royal Statistical Society, Series A for 2006–2007
Faculty Innovation Fund Award, JHSPH, 2006
UCLA Charles E. and Sue K. Young Graduate Student Award, 2003
UCLA Dissertation Year Fellowship, 2002
Winner, ASA Student Paper Competition in Statistical Computing and Graphics, 2002
Teaching Assistant of the Year, UCLA Department of Statistics, 2000
Data science has taken the world by storm. Every field of study and area of business has been affected as people increasingly realize the value of the incredible quantities of data being generated. But to extract value from those data, one needs to be trained in the proper data science skills. The R programming language has become the de facto programming language for data science. Its flexibility, power, sophistication, and expressiveness have made it an invaluable tool for data scientists around the world. This book is about the fundamentals of R programming. You will get started with the basics of the language, learn how to manipulate datasets, how to write functions, and how to debug and optimize code. With the fundamentals provided in this book, you will have a solid foundation on which to build your data science toolbox.
發表於2024-12-24
R Programming for Data Science 2024 pdf epub mobi 電子書 下載
圖書標籤: R 計算機 美國 編程 機器學習 人智 calibre Programming
這書跟著coursera上roger peng的課一起看會比較好,講的比較淺但是蠻適閤初學者快速上手的。入門之後可以再有針對性地看其他的參考書。
評分這書真沒啥營養,好好把R相關的中文版的看完就知道:這本書完全是重復,毫無新意,而且書名字寫的是for data science,但是通篇沒有多少與data science有關的,全是重復彆的書上的基礎內容
評分這書跟著coursera上roger peng的課一起看會比較好,講的比較淺但是蠻適閤初學者快速上手的。入門之後可以再有針對性地看其他的參考書。
評分這書跟著coursera上roger peng的課一起看會比較好,講的比較淺但是蠻適閤初學者快速上手的。入門之後可以再有針對性地看其他的參考書。
評分這書跟著coursera上roger peng的課一起看會比較好,講的比較淺但是蠻適閤初學者快速上手的。入門之後可以再有針對性地看其他的參考書。
R Programming for Data Science 2024 pdf epub mobi 電子書 下載