LEADER 01045nam a2200265 i 4500 001 991001145579707536 008 050712s1999 it 000 0 ita d 020 $a8876703330 035 $ab13327392-39ule_inst 040 $aSet. Economia$bita 082 0 $a332.601 100 1 $aMichalos, Alex C$0265868 245 13$aUn'imposta giusta :$bla Tobin tax : tassare le operazioni finanziarie per costruire una finanza etica /$cAlex C. Michalos ; prefazione di Roberto Panizza ; introduzione di Elsa Fornero 260 $aTorino :$bEGA,$c1999 300 $a142 p. ;$c21 cm 490 $aAltrisaggi ;$v46 650 4$aOperazioni finanziarie$xTributi$xTeorie 700 1 $aFornero, Elsa 700 1 $aPanizza, Roberto 907 $a.b13327392$b10-05-18$c12-07-05 912 $a991001145579707536 945 $aLE025 ECO 332.6 MIC01.01$g1$i2025000134942$lle025$nCatalogato 2018$op$pE10.33$q-$rl$s- $t0$u7$v1$w7$x0$y.i14116431$z01-08-05 996 $aImposta giusta$9663510 997 $aUNISALENTO 998 $ale025$b12-07-05$cm$da $e-$fita$git $h3$i0 LEADER 03747nam 2200421 450 001 9910827499203321 005 20170914034126.0 035 $a(CKB)4100000000880906 035 $a(MiAaPQ)EBC4981589 035 $a(WaSeSS)IndRDA00090926 035 $a(CaSebORM)9781787121393 035 $a(PPN)233408029 035 $a(EXLCZ)994100000000880906 100 $a20170831d2017 uy| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aMastering predictive analytics with R $emachine learning techniques for advanced models /$fJames D. Miller, Rui Miguel Forte 205 $aSecond edition. 210 1$aBirmingham :$cPackt,$d2017. 215 $a1 online resource (449 pages) $cillustrations 300 $aIncludes index. 311 $a1-78712-139-9 311 $a1-78712-435-5 330 $aMaster the craft of predictive modeling in R by developing strategy, intuition, and a solid foundation in essential concepts About This Book Grasping the major methods of predictive modeling and moving beyond black box thinking to a deeper level of understanding Leveraging the flexibility and modularity of R to experiment with a range of different techniques and data types Packed with practical advice and tips explaining important concepts and best practices to help you understand quickly and easily Who This Book Is For Although budding data scientists, predictive modelers, or quantitative analysts with only basic exposure to R and statistics will find this book to be useful, the experienced data scientist professional wishing to attain master level status , will also find this book extremely valuable.. This book assumes familiarity with the fundamentals of R, such as the main data types, simple functions, and how to move data around. Although no prior experience with machine learning or predictive modeling is required, there are some advanced topics provided that will require more than novice exposure. What You Will Learn Master the steps involved in the predictive modeling process Grow your expertise in using R and its diverse range of packages Learn how to classify predictive models and distinguish which models are suitable for a particular problem Understand steps for tidying data and improving the performing metrics Recognize the assumptions, strengths, and weaknesses of a predictive model Understand how and why each predictive model works in R Select appropriate metrics to assess the performance of different types of predictive model Explore word embedding and recurrent neural networks in R Train models in R that can work on very large datasets In Detail R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions. With its constantly growing community and plethora of packages, R offers the functionality to deal with a truly vast array of problems. The book begins with a dedicated chapter on the language of models and the predictive modeling process. You will understand the learning curve and the process of tidying data. Each subsequent chapter tackles a particular type of model, such as neural networks, and focuses on the three important questions of how the model works, how to use R to train it, and how to measure and assess its performance using real-world datasets. How do y... 606 $aR (Computer program language) 615 0$aR (Computer program language) 700 $aMiller$b James D.$0150561 702 $aForte$b Rui Miguel 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910827499203321 996 $aMastering predictive analytics with R$94104923 997 $aUNINA