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Introduces fundamental data science methodologies using the R programming language
Covers concepts through real-world datasets and case studies
Examines cutting edge topics in both research and commercial applications
Includes supplementary material: sn.pub/extras
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Table of contents (8 chapters)
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Front Matter
About this book
The goal of “Beginning Data Science with R” is to introduce the readers to some of the useful data science techniques and their implementation with the R programming language. The book attempts to strike a balance between the how: specific processes and methodologies, and understanding the why: going over the intuition behind how a particular technique works, so that the reader can apply it to the problem at hand. This book will be useful for readers who are not familiar with statistics and the R programming language.
Reviews
“The target audience for this book is non-R programmers and non-statisticians. … if you want to get started with R and/or new statistical procedures have a look at this book. It can be quite helpful.” (David E. Booth, Technometrics, Vol. 58 (2), 2016)
“This book is written for coders who already know how to code to learn R for data science. The book covers how to install and use R … . This is a good book to get you stated coding in R for data science.” (Mary Anne, Cats and Dogs with Data, maryannedata.com, May, 2015)
“A comprehensive, yet short tutorial on practical application of R to the modern data science tasks or projects. … Who I recommend it to: managers who work on data projects, technical team leaders, CS students, Business Intelligence professionals, beginner architects, general computer academia, statisticians, several categories of scientists or researchers as biologists, lab, criminologists, and also Finance pros or actuarials.” (Compudicted, compudicted.wordpress.com, February, 2015)
Authors and Affiliations
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Foster City, USA
Manas A. Pathak
About the author
Bibliographic Information
Book Title: Beginning Data Science with R
Authors: Manas A. Pathak
DOI: https://doi.org/10.1007/978-3-319-12066-9
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing Switzerland 2014
Hardcover ISBN: 978-3-319-12065-2Published: 18 December 2014
Softcover ISBN: 978-3-319-37473-4Published: 30 April 2017
eBook ISBN: 978-3-319-12066-9Published: 08 December 2014
Edition Number: 1
Number of Pages: XI, 157
Number of Illustrations: 129 b/w illustrations, 26 illustrations in colour
Topics: Mathematical and Computational Engineering, Statistics and Computing/Statistics Programs, Signal, Image and Speech Processing