Effective Statistical Learning Methods for Actuaries III is popular PDF and ePub book, written by Michel Denuit in 2019-10-31, it is a fantastic choice for those who relish reading online the Business & Economics genre. Let's immerse ourselves in this engaging Business & Economics book by exploring the summary and details provided below. Remember, Effective Statistical Learning Methods for Actuaries III can be Read Online from any device for your convenience.
Effective Statistical Learning Methods for Actuaries III Book PDF Summary
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.
Detail Book of Effective Statistical Learning Methods for Actuaries III PDF
- Author : Michel Denuit
- Release : 31 October 2019
- Publisher : Springer Nature
- ISBN : 9783030258276
- Genre : Business & Economics
- Total Page : 250 pages
- Language : English
- PDF File Size : 19,6 Mb
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