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
发表于2024-11-27
R Programming for Data Science 2024 pdf epub mobi 电子书
图书标签: R 计算机 美国 编程 机器学习 人智 calibre Programming
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.
读的第一本R语言的书 每一部分都是浅尝辄止 原理讲得不透 好处是篇幅短 读得快
评分这书真没啥营养,好好把R相关的中文版的看完就知道:这本书完全是重复,毫无新意,而且书名字写的是for data science,但是通篇没有多少与data science有关的,全是重复别的书上的基础内容
评分这书真没啥营养,好好把R相关的中文版的看完就知道:这本书完全是重复,毫无新意,而且书名字写的是for data science,但是通篇没有多少与data science有关的,全是重复别的书上的基础内容
评分这书真没啥营养,好好把R相关的中文版的看完就知道:这本书完全是重复,毫无新意,而且书名字写的是for data science,但是通篇没有多少与data science有关的,全是重复别的书上的基础内容
评分这书真没啥营养,好好把R相关的中文版的看完就知道:这本书完全是重复,毫无新意,而且书名字写的是for data science,但是通篇没有多少与data science有关的,全是重复别的书上的基础内容
R Programming for Data Science 2024 pdf epub mobi 电子书