Hidden Bibliographic Details
| Varying Form of Title: | Neural networks and extensions
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| Other authors / contributors: | Hainaut, Donatien, author.
Trufin, Julien, author.
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| ISBN: | 9783030258276
3030258270
3030258262
9783030258269
9783030258283
3030258289
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| Digital file characteristics: | text file PDF
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| Notes: | Includes bibliographical references.
Online resource; title from PDF title page (SpringerLink, viewed November 6, 2019).
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| Summary: | 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.
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| Other form: | Print version: 9783030258269
Print version: 9783030258283
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| Standard no.: | 10.1007/978-3-030-25827-6
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