1.

Record Nr.

UNISA996416847203316

Autore

Denuit Michel

Titolo

Effective Statistical Learning Methods for Actuaries III [[electronic resource] ] : Neural Networks and Extensions / / by Michel Denuit, Donatien Hainaut, Julien Trufin

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019

ISBN

3-030-25827-0

Edizione

[1st ed. 2019.]

Descrizione fisica

1 online resource (258 pages) : illustrations

Collana

Springer Actuarial Lecture Notes, , 2523-3289

Disciplina

368.01

Soggetti

Actuarial science

Statistics 

Neural networks (Computer science) 

Actuarial Sciences

Statistics for Business, Management, Economics, Finance, Insurance

Mathematical Models of Cognitive Processes and Neural Networks

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

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.

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 learning. .

2.

Record Nr.

UNIORUON00047244

Autore

LANDAU, Jacob M.

Titolo

An Arab anti-turk handbill, 1881 / Jacob M. Landau

Pubbl/distr/stampa

221-227 pp. ; 23 cm

Edizione

[Strasbourg : Institut d'Etudes tourques de l'Université de Strasbourg]

Descrizione fisica

Estratto da Turcica. 9,1 (1977)

Classificazione

OTT IV

Soggetti

NAZIONALISMO ARABO

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia