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ISBN 10: 3031124111 ISBN 13: 9783031124112
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Paperback or Softback. Condizione: New. Statistical Foundations of Actuarial Learning and Its Applications. Book.
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Aggiungi al carrelloPaperback. Condizione: New. Brand New! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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Aggiungi al carrelloPaperback. Condizione: Brand New. 617 pages. 9.25x6.10x1.22 inches. In Stock.
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ISBN 10: 3031124111 ISBN 13: 9783031124112
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware -This open access book discusses the statistical modeling of insurance problems, a process which comprises data collection, data analysis and statistical model building to forecast insured events that may happen in the future. It presents the mathematical foundations behind these fundamental statistical concepts and how they can be applied in daily actuarial practice.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 620 pp. Englisch.
Lingua: Inglese
Editore: Springer International Publishing, Springer International Publishing, 2022
ISBN 10: 3031124111 ISBN 13: 9783031124112
Da: AHA-BUCH GmbH, Einbeck, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This open access book discusses the statistical modeling of insurance problems, a process which comprises data collection, data analysis and statistical model building to forecast insured events that may happen in the future. It presents the mathematical foundations behind these fundamental statistical concepts and how they can be applied in daily actuarial practice. Statistical modeling has a wide range of applications, and, depending on the application, the theoretical aspects may be weighted differently: here the main focus is on prediction rather than explanation. Starting with a presentation of state-of-the-art actuarial models, such as generalized linear models, the book then dives into modern machine learning tools such as neural networks and text recognition to improve predictive modeling with complex features. Providing practitioners with detailed guidance on how to apply machine learning methods to real-world data sets, and how to interpret the results without losing sight of the mathematical assumptions on which these methods are based, the book can serve as a modern basis for an actuarial education syllabus.
Lingua: Inglese
Editore: Springer International Publishing AG, CH, 2022
ISBN 10: 3031124111 ISBN 13: 9783031124112
Da: Rarewaves.com UK, London, Regno Unito
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Statistical Foundations of Actuarial Learning and its Applications | Mario V. Wüthrich (u. a.) | Taschenbuch | XII | Englisch | 2022 | Springer | EAN 9783031124112 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
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Lingua: Inglese
Editore: Springer International Publishing, Springer International Publishing Nov 2022, 2022
ISBN 10: 3031124111 ISBN 13: 9783031124112
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 42,79
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This open access book discusses the statistical modeling of insurance problems, a process which comprises data collection, data analysis and statistical model building to forecast insured events that may happen in the future. It presents the mathematical foundations behind these fundamental statistical concepts and how they can be applied in daily actuarial practice. Statistical modeling has a wide range of applications, and, depending on the application, the theoretical aspects may be weighted differently: here the main focus is on prediction rather than explanation. Starting with a presentation of state-of-the-art actuarial models, such as generalized linear models, the book then dives into modern machine learning tools such as neural networks and text recognition to improve predictive modeling with complex features. Providing practitioners with detailed guidance on how to apply machine learning methods to real-world data sets, and how to interpret the results without losing sight of the mathematical assumptions on which these methods are based, the book can serve as a modern basis for an actuarial education syllabus. 620 pp. Englisch.
Lingua: Inglese
Editore: Springer International Publishing, 2022
ISBN 10: 3031124111 ISBN 13: 9783031124112
Da: moluna, Greven, Germania
EUR 39,60
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book is open access, which means that you have free and unlimited accessUniquely combines classical statistical modeling with modern machine learning methodsDiscusses the state-of-the-art in predictive modeling for actuarial work.