r_in_a_nutshell_2nd_edition_by_joseph_adler

R in a Nutshell, 2nd Edition by Joseph Adler

Book Summary

“If you’re considering R for statistical computing and R data visualization, this book provides a quick and practical R guide to just about everything R you can do with the open source R language and R software environment. You’ll learn how to write R functions and use R packages to R help you prepare, R visualize, and R analyze data. R Author Joseph Adler illustrates each R process with a wealth of R examples from R for medicine, R for business, and R for sports.” (RNuts 2012)

R Updated for R 2.14 and R 2.15, this second edition includes new and expanded chapters on R performance, the R ggplot2 data visualization package, and parallel R R computing with [[Hadoop.

About the Author

Joseph Adler has many years of experience in R data mining and [R data analysis]] at companies including DoubleClick, American Express, and VeriSign. He graduated from MIT with an Sc.B and M.Eng in Computer Science and Electrical Engineering from MIT. He is the inventor of several patents for computer security and cryptography, and the author of Baseball Hacks. Currently, he is a senior data scientist at LinkedIn.

Product Details

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Fair Use Sources

R: R Fundamentals, R Inventor - R Language Designer: Ross Ihaka and Robert Gentleman in August 1993; R Core Team, R Language Definition on R-Project.org, R reserved words (R keywords), R data structures - R algorithms, R syntax, R input and Output, R data transformations, R probability, R statistics, R linear regression (ANOVA), R time series analysis, R graphics, R markdown, R OOP, R on Linux, R on macOS, R on Windows, R installation, R containerization, R configuration, R compiler - R interpreter (R REPL), R IDEs (RStudio, Jupyter Notebook), R development tools, R DevOps - R SRE, R data science - R DataOps, R machine learning, R deep learning, Functional R, R concurrency, R history, R bibliography, R glossary, R topics, R courses, R Standard Library, R libraries, R packages (tidyverse package), R frameworks, RDocumentation.org / CRAN, R research, R GitHub, Written in R, R popularity, R Awesome list, R Versions, Python. (navbar_r)



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