LEADER 02256nam 2200613 a 450 001 9910460355303321 005 20200520144314.0 010 $a1-935476-34-3 010 $a1-283-05720-4 010 $a9786613057204 010 $a1-935476-35-1 035 $a(CKB)2670000000081247 035 $a(EBL)3383910 035 $a(SSID)ssj0000471765 035 $a(PQKBManifestationID)12164519 035 $a(PQKBTitleCode)TC0000471765 035 $a(PQKBWorkID)10427729 035 $a(PQKB)10341553 035 $a(MiAaPQ)EBC3383910 035 $a(Au-PeEL)EBL3383910 035 $a(CaPaEBR)ebr10457081 035 $a(CaONFJC)MIL305720 035 $a(OCoLC)711685231 035 $a(EXLCZ)992670000000081247 100 $a20110131d2011 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 14$aThe nurse's social media advantage$b[electronic resource] $ehow making connections and sharing ideas can enhance your nursing practice /$fby Robert Fraser 210 $aIndianapolis, Ind. $cSigma Theta Tau International$dc2011 215 $a1 online resource (256 p.) 300 $aDescription based upon print version of record. 311 $a1-935476-01-7 320 $aIncludes bibliographical references. 327 $aLaying the foundation -- Understanding the basic building blocks of social media -- Privacy, disclaimers, and professional issues, oh my -- Improve the way you access the internet -- Dealing with the overload -- Developing your online reputation -- Begin to share your knowledge -- Creating quality content -- Building your online network -- Where to from here?. 606 $aNursing informatics 606 $aMedical care$xComputer network resources 606 $aInternet 608 $aElectronic books. 615 0$aNursing informatics. 615 0$aMedical care$xComputer network resources. 615 0$aInternet. 676 $a610.730285 700 $aFraser$b Robert$f1986-$0133696 712 02$aSigma Theta Tau International. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910460355303321 996 $aThe nurse's social media advantage$91963744 997 $aUNINA LEADER 00987nam0 22002531i 450 001 UON00180965 005 20231205103131.747 100 $a20030730d1972 |0itac50 ba 101 $aeng 102 $aUS 105 $a|||| 1|||| 200 1 $aˆThe ‰Nixon doctrine$fMelvin R. 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Schelling 210 $aWashington$cTown Hall Meeting$d1972 - 79 p. ; 19 cm. 606 $aNIXON RICHARD$3UONC037242$2FI 700 1$aLAIRD$bMelvin R.$3UONV103972$0675649 702 1$aGRIFFIN$bRobert P.$3UONV103974 702 1$aMCGEE$bGale W.$3UONV103973 702 1$aSCHELLING$bThomas C.$3UONV103975 801 $aIT$bSOL$c20240220$gRICA 899 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$2UONSI 912 $aUON00180965 950 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$dSI IV POL A 1318 $eSI SC 20766 5 1318 996 $aNixon doctrine$91289388 997 $aUNIOR LEADER 03991nam 2200613 450 001 9910824972803321 005 20220223214314.0 010 $a1-68015-358-7 010 $a1-78216-215-1 035 $a(CKB)2550000001138614 035 $a(OCoLC)862380117 035 $a(CaPaEBR)ebrary10794279 035 $a(SSID)ssj0001139763 035 $a(PQKBManifestationID)11649255 035 $a(PQKBTitleCode)TC0001139763 035 $a(PQKBWorkID)11220486 035 $a(PQKB)11737178 035 $a(Au-PeEL)EBL1343653 035 $a(CaPaEBR)ebr10794279 035 $a(CaONFJC)MIL538284 035 $a(CaSebORM)9781782162148 035 $a(MiAaPQ)EBC1343653 035 $a(PPN)227990579 035 $a(EXLCZ)992550000001138614 100 $a20111102d2013 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aMachine learning with R /$fBrett Lantz 205 $a1st edition 210 1$aBirmingham :$cPackt Publishing,$d2013. 215 $a1 online resource (396 p.) 225 1 $aCommunity experience distilled 300 $aIncludes index. 311 $a1-78216-214-3 311 $a1-306-07033-3 330 $aR gives you access to the cutting-edge software you need to prepare data for machine learning. No previous knowledge required ? this book will take you methodically through every stage of applying machine learning. Harness the power of R for statistical computing and data science Use R to apply common machine learning algorithms with real-world applications Prepare, examine, and visualize data for analysis Understand how to choose between machine learning models Packed with clear instructions to explore, forecast, and classify data In Detail Machine learning, at its core, is concerned with transforming data into actionable knowledge. This fact makes machine learning well-suited to the present-day era of "big data" and "data science". Given the growing prominence of R?a cross-platform, zero-cost statistical programming environment?there has never been a better time to start applying machine learning. Whether you are new to data science or a veteran, machine learning with R offers a powerful set of methods for quickly and easily gaining insight from your data. "Machine Learning with R" is a practical tutorial that uses hands-on examples to step through real-world application of machine learning. Without shying away from the technical details, we will explore Machine Learning with R using clear and practical examples. Well-suited to machine learning beginners or those with experience. Explore R to find the answer to all of your questions. How can we use machine learning to transform data into action? Using practical examples, we will explore how to prepare data for analysis, choose a machine learning method, and measure the success of the process. We will learn how to apply machine learning methods to a variety of common tasks including classification, prediction, forecasting, market basket analysis, and clustering. By applying the most effective machine learning methods to real-world problems, you will gain hands-on experience that will transform the way you think about data. "Machine Learning with R" will provide you with the analytical tools you need to quickly gain insight from complex data. 410 0$aCommunity experience distilled. 606 $aMachine learning$xStatistical methods$vHandbooks, manuals, etc 606 $aR (Computer program language)$vHandbooks, manuals, etc 606 $aProgramming languages (Electronic computers) 615 0$aMachine learning$xStatistical methods 615 0$aR (Computer program language) 615 0$aProgramming languages (Electronic computers) 700 $aLantz$b Brett$01466983 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910824972803321 996 $aMachine learning with R$94023486 997 $aUNINA