LEADER 01077nam0 22003013i 450 001 USM1700502 005 20231121125916.0 010 $a9780471731733 100 $a20130222d2007 ||||0itac50 ba 101 | $aeng 102 $aus 181 1$6z01$ai $bxxxe 182 1$6z01$an 200 1 $aCapital ideas evolving$f Peter L. Bernstein 210 $aHoboken (N.J.)$cJohn Wiley & Sons$d2007 215 $aXXI, 282 p., [4] c. di tav.$cill.$d24 cm 606 $aBorse$xStati Uniti d'America$2FIR$3SBLC029150$9I 676 $a332.632$9$v21 700 1$aBernstein$b, Peter L.$3SBLV010228$4070$0116786 790 1$aBernstein$b, Peter$3MILV187366$zBernstein, Peter L. 801 3$aIT$bIT-01$c20130222 850 $aIT-FR0098 899 $aBiblioteca Area Giuridico Economica$bFR0098 912 $aUSM1700502 950 0$aBiblioteca Area Giuridico Economica$d 53DEG B. P. 15$e 53DEG0000001015 VMN NN $fB $h20120101$i20130222 977 $a 53 996 $aCapital ideas evolving$93642786 997 $aUNICAS LEADER 04029nam 22007575 450 001 9910633918303321 005 20251009102734.0 010 $a3-031-16990-5 024 7 $a10.1007/978-3-031-16990-8 035 $a(MiAaPQ)EBC7150159 035 $a(Au-PeEL)EBL7150159 035 $a(CKB)25504224600041 035 $a(PPN)266349005 035 $a(DE-He213)978-3-031-16990-8 035 $a(OCoLC)1352422294 035 $a(EXLCZ)9925504224600041 100 $a20221129d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning for Practical Decision Making $eA Multidisciplinary Perspective with Applications from Healthcare, Engineering and Business Analytics /$fby Christo El Morr, Manar Jammal, Hossam Ali-Hassan, Walid EI-Hallak 205 $a1st ed. 2022. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022. 215 $a1 online resource (475 pages) 225 1 $aInternational Series in Operations Research & Management Science,$x2214-7934 ;$v334 311 08$aPrint version: El Morr, Christo Machine Learning for Practical Decision Making Cham : Springer International Publishing AG,c2023 9783031169892 320 $aIncludes bibliographical references and index. 327 $a1. Introduction to Machine Learning -- 2. Statistics -- 3. Overview of Machine Learning Algorithms -- 4. Data Preprocessing -- 5. Data Visualization -- 6. Linear Regression -- 7. Logistic Regression -- 8. Decision Trees -- 9. Naïve Bayes -- 10. K-Nearest Neighbors -- 11. Neural Networks -- 12. K-Means -- 13. Support Vector Machine -- 14. Voting and Bagging -- 15. Boosting and Stacking -- 16. Future Directions and Ethical Considerations. 330 $aThis book provides a hands-on introduction to Machine Learning (ML) from a multidisciplinary perspective that does not require a background in data science or computer science. It explains ML using simple language and a straightforward approach guided by real-world examples in areas such as health informatics, information technology, and business analytics. The book will help readers understand the various key algorithms, major software tools, and their applications. Moreover, through examples from the healthcare and business analytics fields, it demonstrates how and when ML can help them make better decisions in their disciplines. The book is chiefly intended for undergraduate and graduate students who are taking an introductory course in machine learning. It will also benefit data analysts and anyone interested in learning ML approaches. 410 0$aInternational Series in Operations Research & Management Science,$x2214-7934 ;$v334 606 $aOperations research 606 $aHealth services administration 606 $aMedical informatics 606 $aMachine learning 606 $aArtificial intelligence 606 $aBusiness$xData processing 606 $aOperations Research and Decision Theory 606 $aHealth Care Management 606 $aHealth Informatics 606 $aMachine Learning 606 $aArtificial Intelligence 606 $aBusiness Analytics 615 0$aOperations research. 615 0$aHealth services administration. 615 0$aMedical informatics. 615 0$aMachine learning. 615 0$aArtificial intelligence. 615 0$aBusiness$xData processing. 615 14$aOperations Research and Decision Theory. 615 24$aHealth Care Management. 615 24$aHealth Informatics. 615 24$aMachine Learning. 615 24$aArtificial Intelligence. 615 24$aBusiness Analytics. 676 $a658.403 676 $a658.4030285631 700 $aEl Morr$b Christo$f1966-$0930155 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910633918303321 996 $aMachine learning for practical decision making$93088865 997 $aUNINA