Andere Kunden interessierten sich auch für
![Effective Statistical Learning Methods for Actuaries II]( "Effective Statistical Learning Methods for Actuaries II")
Effective Statistical Learning Methods for Actuaries II53,49 €![Effective Statistical Learning Methods for Actuaries I]( "Effective Statistical Learning Methods for Actuaries I")
Effective Statistical Learning Methods for Actuaries I37,99 €![Mathematical and Statistical Methods for Actuarial Sciences and Finance]( "Mathematical and Statistical Methods for Actuarial Sciences and Finance")
Mathematical and Statistical Methods for Actuarial Sciences and Finance81,99 €![Surplus Analysis of Sparre Andersen Insurance Risk Processes]( "Surplus Analysis of Sparre Andersen Insurance Risk Processes")
Surplus Analysis of Sparre Andersen Insurance Risk Processes64,99 €![Surplus Analysis of Sparre Andersen Insurance Risk Processes]( "Surplus Analysis of Sparre Andersen Insurance Risk Processes")
Surplus Analysis of Sparre Andersen Insurance Risk Processes64,99 €![Actuarial Aspects of Long Term Care]( "Actuarial Aspects of Long Term Care")
Actuarial Aspects of Long Term Care103,99 €![Explaining Currency Crises: A Statistical Machine Learning Approach]( "Explaining Currency Crises: A Statistical Machine Learning Approach")
Explaining Currency Crises: A Statistical Machine Learning Approach56,99 €
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.
Requiring only a basic knowledge of statistics, this book is written for masters students in the actuarial sciences and for actuaries wishing to update their skills in machine learning.
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.
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.
Requiring only a basic knowledge of statistics, this book is written for masters students in the actuarial sciences and for actuaries wishing to update their skills in machine learning.
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.
"Intended for students and practicing actuaries, this book follows its presentations of neural network methods with detailed case studies using insurance data. ... The unified approach lays a solid foundation for understanding non-likelihood methods readers may later encounter." (David R. Bickel, Mathematical Reviews, May, 2021)