000 04041nam a22004695i 4500
001 vtls000541708
003 RU-ToGU
005 20210922082318.0
007 cr nn 008mamaa
008 160915s2014 xxu| s |||| 0|eng d
020 _a9781493917020
_9978-1-4939-1702-0
024 7 _a10.1007/978-1-4939-1702-0
_2doi
035 _ato000541708
040 _aSpringer
_cSpringer
_dRU-ToGU
050 4 _aQA276-280
072 7 _aUFM
_2bicssc
072 7 _aCOM077000
_2bisacsh
082 0 4 _a519.5
_223
100 1 _aOhri, A.
_eauthor.
_9448100
245 1 0 _aR for Cloud Computing
_helectronic resource
_bAn Approach for Data Scientists /
_cby A Ohri.
260 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2014.
300 _aXVII, 267 p. 255 illus., 160 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
505 0 _aIntroduction -- An Approach for Data Scientists -- Navigating the Choices in R and Cloud Computing -- Setting up R on the Cloud -- Using R -- Using R with Data and Bigger Data -- R with Cloud APIs -- Securing your R Cloud -- Training Literature for Cloud Computing and R.
520 _aR 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.
650 0 _aStatistics.
_9124796
650 0 _aComputer Science.
_9155490
650 0 _aMathematical statistics.
_9566264
650 0 _aEconomics
_xStatistics.
_9304057
650 1 4 _aStatistics.
_9124796
650 2 4 _aStatistics and Computing/Statistics Programs.
_9303277
650 2 4 _aStatistics for Business/Economics/Mathematical Finance/Insurance.
_9304058
650 2 4 _aProgramming Languages, Compilers, Interpreters.
_9303287
710 2 _aSpringerLink (Online service)
_9143950
773 0 _tSpringer eBooks
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4939-1702-0
912 _aZDB-2-SMA
999 _c399970