LEADER 00915nam0 22002893i 450 001 996285350303316 005 20190212112838.0 010 $a978-88-6959-718-3 100 $a20170524d2017----||||0itac50 ba 101 $aita 102 $aIT 200 1 $a<> nuovi volti del terrore$edal terrorismo islamico al cyber terrorismo$efenomenologia di una perturbante forma di violenza$fMaria Novella Campagnoli 210 $aVicalvi (FR)$cKey$d2017 215 $a112 p.$d21 cm 225 $aNunca mas$v7 410 0$aNunca mas$fcollana diretta da Guendalina Scozzafava$v7 606 0 $aCyberterrorismo$2BNCF 606 0 $aTerrorismo islamico$2BNCF 676 $a363.325 700 1$aCAMPAGNOLI,$bMaria Novella$0761941 801 0$aIT$bsalbc$gISBD 912 $a996285350303316 951 $aP13 1289$b488 DISA 959 $aBK 969 $aDISTRA 996 $aNuovi volti del terrore$91543185 997 $aUNISA LEADER 04261nam 22006855 450 001 9910734891903321 005 20250610113331.0 010 $a9783031387470 010 $a3031387473 024 7 $a10.1007/978-3-031-38747-0 035 $a(MiAaPQ)EBC30614337 035 $a(Au-PeEL)EBL30614337 035 $a(DE-He213)978-3-031-38747-0 035 $a(PPN)272261017 035 $a(CKB)27357707800041 035 $a(EXLCZ)9927357707800041 100 $a20230630d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 13$aAn Introduction to Statistical Learning $ewith Applications in Python /$fby Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani, Jonathan Taylor 205 $a1st ed. 2023. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource (617 pages) 225 1 $aSpringer Texts in Statistics,$x2197-4136 300 $aIncludes index. 311 08$aPrint version: James, Gareth An Introduction to Statistical Learning Cham : Springer International Publishing AG,c2023 9783031387463 327 $aIntroduction -- Statistical Learning -- Linear Regression -- Classification -- Resampling Methods -- Linear Model Selection and Regularization -- Moving Beyond Linearity -- Tree-Based Methods -- Support Vector Machines -- Deep Learning -- Survival Analysis and Censored data -- Unsupervised Learning -- Multiple Testing -- Index. 330 $aAn Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users. 410 0$aSpringer Texts in Statistics,$x2197-4136 606 $aStatistics 606 $aMathematical statistics$xData processing 606 $aStatistics 606 $aStatistical Theory and Methods 606 $aStatistics and Computing 606 $aApplied Statistics 606 $aEstadística matemātica$2thub 606 $aModels matemātics$2thub 606 $aPython (Llenguatge de programaciķ)$2thub 608 $aLlibres electrōnics$2thub 615 0$aStatistics. 615 0$aMathematical statistics$xData processing. 615 0$aStatistics. 615 14$aStatistical Theory and Methods. 615 24$aStatistics and Computing. 615 24$aApplied Statistics. 615 7$aEstadística matemātica 615 7$aModels matemātics 615 7$aPython (Llenguatge de programaciķ) 676 $a511.8 700 $aJames$b Gareth$f1936-$01802859 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910734891903321 996 $aAn Introduction to Statistical Learning$94349166 997 $aUNINA