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[null,"1.","Record Nr.",null,"UNISA996416847203316"]
[null,null,"Autore",null,"Denuit Michel"]
[null,null,"Titolo",null,"Effective Statistical Learning Methods for Actuaries III [[electronic resource] ] : Neural Networks and Extensions / / by Michel Denuit, Donatien Hainaut, Julien Trufin"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019"]
[null,null,"ISBN",null,"3-030-25827-0"]
[null,null,"Edizione",null,"[1st ed. 2019.]"]
[null,null,"Descrizione fisica",null,"1 online resource (258 pages) : illustrations"]
[null,null,"Collana",null,"Springer Actuarial Lecture Notes, , 2523-3289"]
[null,null,"Disciplina",null,"368.01"]
[null,null,"Soggetti",null,"Actuarial science"]
[{"$nulls":4},"Statistics "]
[{"$nulls":4},"Neural networks (Computer science) "]
[{"$nulls":4},"Actuarial Sciences"]
[{"$nulls":4},"Statistics for Business, Management, Economics, Finance, Insurance"]
[{"$nulls":4},"Mathematical Models of Cognitive Processes and Neural Networks"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Preface. - Feed-forward Neural Networks. - Byesian Neural Networks and GLM. - Deep Neural Networks -- Dimension-Reduction with Forward Neural Nets Applied to Mortality. - Self-organizing Maps and k-means clusterin in non Life Insurance. - Ensemble of Neural Networks -- Gradient Boosting with Neural Networks. - Time Series Modelling with Neural Networks -- References."]
[null,null,null,"Sommario/riassunto","Artificial intelligence and neural networks offer a powerful alternative to statistical methods for analyzing data. This book reviews some of the most recent developments in neural networks, with a focus on applications in actuarial sciences and finance. The third volume of the trilogy simultaneously introduces the relevant tools for developing and analyzing neural networks, in a style that is mathematically rigorous and yet accessible. The authors proceed by successive generalizations, requiring of the reader only a basic knowledge of statistics. Various topics are covered from feed-forward networks to deep learning, such as Bayesian learning, boosting methods and Long Short Term Memory models. All methods are applied to claims, mortality or time-series forecasting. This book is written for masters students in the actuarial sciences and for actuaries wishing to update their skills in machine "]
[{"$nulls":4},"learning. ."]
[null,"2.","Record Nr.",null,"UNINA9910795028003321"]
[null,null,"Autore",null,"Sabando Suarez Pedro"]
[null,null,"Titolo",null,"Así se creó el Sistema Nacional de Salud (SNS) / / Pedro Sabando Suarez"]
[null,null,"Pubbl/distr/stampa",null,"Madrid : , : Ediciones Diaz de Santos S.A., , [2020]"]
[{"$nulls":4},"©2020"]
[null,null,"ISBN",null,"84-9052-240-5"]
[null,null,"Descrizione fisica",null,"1 online resource (261 pages)"]
[null,null,"Disciplina",null,"362.10946"]
[null,null,"Soggetti",null,"Public health - Spain - History"]
[{"$nulls":4},"National health services - Spain - History"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]