Beginning Data Science with R
(Sprache: Englisch)
"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...
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Produktinformationen zu „Beginning Data Science with R “
Klappentext zu „Beginning Data Science with R “
"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.
Inhaltsverzeichnis zu „Beginning Data Science with R “
- From the Contents: Part I Tools and Techniques- Setting up your R development environment
- Overview of the R programming language
- Getting Data into R
- Interfacing with Other Environments
Part II Data Analysis
- Exploratory Data Analysis
- Statistical Modeling
- Linear Regression and Generalized Linear Models
- Hypothesis Testing
- Time Series Data
- Text Mining
- Social Network Data
- Big Data
Autoren-Porträt von Manas A. Pathak
Manas A. Pathaks is a Research Scientist at Adchemy, Inc., and a former researcher from CMU in signal processing and computer science.
Bibliographische Angaben
- Autor: Manas A. Pathak
- 2014, 2014, XI, 157 Seiten, 26 farbige Abbildungen, Masse: 16 x 24,1 cm, Gebunden, Englisch
- Verlag: Springer, Berlin
- ISBN-10: 3319120654
- ISBN-13: 9783319120652
- Erscheinungsdatum: 18.12.2014
Sprache:
Englisch
Pressezitat
"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 scientistsor researchers as biologists, lab, criminologists, and also Finance pros or actuarials." (Compudicted, compudicted.wordpress.com, February, 2015)
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