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1. |
Record Nr. |
UNISA996416847203316 |
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Autore |
Denuit Michel |
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Titolo |
Effective Statistical Learning Methods for Actuaries III [[electronic resource] ] : Neural Networks and Extensions / / by Michel Denuit, Donatien Hainaut, Julien Trufin |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
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ISBN |
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Edizione |
[1st ed. 2019.] |
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Descrizione fisica |
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1 online resource (258 pages) : illustrations |
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Collana |
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Springer Actuarial Lecture Notes, , 2523-3289 |
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Disciplina |
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Soggetti |
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Actuarial science |
Statistics |
Neural networks (Computer science) |
Actuarial Sciences |
Statistics for Business, Management, Economics, Finance, Insurance |
Mathematical Models of Cognitive Processes and Neural Networks |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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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. |
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Sommario/riassunto |
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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 |
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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 learning. . |
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2. |
Record Nr. |
UNIORUON00047244 |
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Autore |
LANDAU, Jacob M. |
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Titolo |
An Arab anti-turk handbill, 1881 / Jacob M. Landau |
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Pubbl/distr/stampa |
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Edizione |
[Strasbourg : Institut d'Etudes tourques de l'Université de Strasbourg] |
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Descrizione fisica |
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Estratto da Turcica. 9,1 (1977) |
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Classificazione |
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Soggetti |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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