R for Cloud Computing: An Approach for Data Scientists Paperback - 2014
by A Ohri
- Used
- very good
- Paperback
Description
Standard delivery: 14 to 28 days
About AMMAREAL France
Ammareal is a professional bookseller specialized in used books. We ship worldwide. We have more than 1 million books in stock, including a large number of technical and university-level books. We give back up to 15% of the price of each book to charities, libraries and organizations fighting in favor of literacy. What we do not sell, we give ; what we do not give, we recycle.
Details
- Title R for Cloud Computing: An Approach for Data Scientists
- Author A Ohri
- Binding Paperback
- Condition Used - Very Good
- Pages 267
- Volumes 1
- Language ENG
- Publisher Springer
- Date 2014
- Bookseller's Inventory # C-719-575
- ISBN 9781493917013 / 1493917013
- Weight 0.9 lbs (0.41 kg)
- Dimensions 9.21 x 6.14 x 0.6 in (23.39 x 15.60 x 1.52 cm)
-
Themes
- Aspects (Academic): Science/Technology Aspects
- Library of Congress subjects Cloud computing
- Library of Congress Catalog Number 2014950411
- Dewey Decimal Code 330.015
From the rear cover
R for Cloud Computing looks at some of the tasks performed by business analysts on the desktop (PC era) and helps the user navigate the wealth of information in R and its 4000 packages as well as transition the same analytics using the cloud. With this information the reader can select both cloud vendors and the sometimes confusing cloud ecosystem as well as the R packages that can help process the analytical tasks with minimum effort and cost, and maximum usefulness and customization. The use of Graphical User Interfaces (GUI) and Step by Step screenshot tutorials is emphasized in this book to lessen the famous learning curve in learning R and some of the needless confusion created in cloud computing that hinders its widespread adoption. This will help you kick-start analytics on the cloud including chapters on cloud computing, R, common tasks performed in analytics, scrutiny of big data analytics, and setting up and navigating cloud providers.
Readers are exposed to a breadth of cloud computing choices and analytics topics without being buried in needless depth. The included references and links allow the reader to pursue business analytics on the cloud easily. It is aimed at practical analytics and is easy to transition from existing analytical set up to the cloud on an open source system based primarily on R.
This book is aimed at industry practitioners with basic programming skills and students who want to enter analytics as a profession. Note the scope of the book is neither statistical theory nor graduate level research for statistics, but rather it is for business analytics practitioners. It will also help researchers and academics but at a practical rather than conceptual level.
The R statistical software is the fastest growing analytics platform in the world, and is established in both academia and corporations for robustness, reliability and accuracy. The cloud computing paradigm is firmly established as the next generation of computing from microprocessors to desktop PCs to cloud.
