Free PDF Beginning Data Science with R, by Manas A. Pathak
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Beginning Data Science with R, by Manas A. Pathak
Free PDF Beginning Data Science with R, by Manas A. Pathak
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“We live in the age of data. In the last few years, the methodology of extracting insights from data or "data science" has emerged as a discipline in its own right. The R programming language has become one-stop solution for all types of data analysis. The growing popularity of R is due its statistical roots and a vast open source package library.
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.
- Sales Rank: #3427993 in eBooks
- Published on: 2014-12-08
- Released on: 2014-12-08
- Format: Kindle eBook
Review
“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)
From the Back Cover
“Data Science with R” deals with implementing many useful data analysis methodologies with the R programming language. The target audience for this book is non-R programmers and non-statisticians. The book will cover all the necessary concepts from the basics to state-of-the-art technologies like working with big data. The author attempts to strike a balance between the “how”: specific processes and methodologies, while also talking about the “why”: giving an intuition behind how a particular technique works, so that the reader can apply the generalized solution to the problem at hand.
About the Author
Dr. Manas A. Pathak received a BTech degree in computer science from Visvesvaraya National Institute of Technology, Nagpur, India, in 2006, and MS and PhD degrees from the Language Technologies Institute at Carnegie Mellon University (CMU) in 2009 and 2012 respectively. His PhD thesis on "Privacy-Preserving Machine Learning for Speech Processing" was published as a monograph in the Springer best thesis series. His research received significant press coverage, including articles in the Economist and MIT Tech Review. He has many years of experience with data analysis using the R programming language. He is currently working as a staff software engineer at @WalmartLabs.
Most helpful customer reviews
4 of 7 people found the following review helpful.
Unobjectionable book, terrible value for money
By Dimitri Shvorob
Springer employees who decided to charge a hundred bucks for an unremarkable, thin - only 150 pages! - introduction to R are clearly out of their minds. Let them sort out their problems - the book's author ought to get involved, as this pricing is guaranteed to kill sales of his book - and check out "R in Action" by Robert Kabacoff or "R for Everyone" by Jared Lander instead.
UPD. With the benefit of a little more life experience, I would say: don't spend your time on *any* R book. Python is the way to go.
0 of 4 people found the following review helpful.
Useful starting point for R
By Two Minute Warning
Great book, helped me get up and running successfully for my project. Was easy to follow and was able to use the examples well.
Will recommend for anyone who want to get started with R.
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