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Effective Statistical Learning Methods for Actuaries III: Neural Networks and Extensions
Paperback
Business GeneralGeneral Mathematics
ISBN13: 9783030258269
Publisher: Springer
Published: Nov 13 2019
Pages: 250
Weight: 0.83
Height: 0.56 Width: 6.14 Depth: 9.21
Language: English
This book reviews some of the most recent developments in neural networks, with a focus on applications in actuarial sciences and finance. It simultaneously introduces the relevant tools for developing and analyzing neural networks, in a style that is mathematically rigorous yet accessible.
Artificial intelligence and neural networks offer a powerful alternative to statistical methods for analyzing data. 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 is the third of three volumes entitled Effective Statistical Learning Methods for Actuaries. Written by actuaries for actuaries, this series offers a comprehensive overview of insurance data analytics with applications to P&C, life and health insurance. Although closely related to the other two volumes, this volume can be read independently.
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