An Invitation for Actuaries to join this journey. While Deep Learning has shown remarkable success in the area of unstructured data like image classification, text analysis and speech recognition, there is very little literature on Deep Learning performed on structured/relational data. This investigation also focuses on applying Deep Learning on structured data because actuaries are more comfortable with structured data than unstructured data and so it can be a useful imitative step for other actuaries to apply Deep Learning to solve their own business problems.
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Syed Danish Ali has more than 75 publications across a range of international platforms and is a regular contributor to various research activities in IFoA, CAS, SOA and International Actuarial Association including the ASTIN journal. His non-actuarial publications include articles in Data Science,Quantitative Finance and Social Sciences
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Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -An Invitation for Actuaries to join this journey. While Deep Learning has shown remarkable success in the area of unstructured data like image classification, text analysis and speech recognition, there is very little literature on Deep Learning performed on structured/relational data. This investigation also focuses on applying Deep Learning on structured data because actuaries are more comfortable with structured data than unstructured data and so it can be a useful imitative step for other actuaries to apply Deep Learning to solve their own business problems. 84 pp. Englisch. Bestandsnummer des Verkäufers 9783659961878
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - An Invitation for Actuaries to join this journey. While Deep Learning has shown remarkable success in the area of unstructured data like image classification, text analysis and speech recognition, there is very little literature on Deep Learning performed on structured/relational data. This investigation also focuses on applying Deep Learning on structured data because actuaries are more comfortable with structured data than unstructured data and so it can be a useful imitative step for other actuaries to apply Deep Learning to solve their own business problems. Bestandsnummer des Verkäufers 9783659961878
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Paperback. Zustand: Brand New. 84 pages. 8.66x5.91x0.19 inches. In Stock. Bestandsnummer des Verkäufers 3659961876
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ali Syed DanishSyed Danish Ali has more than 75 publications across a range of international platforms and is a regular contributor to various research activities in IFoA, CAS, SOA and International Actuarial Association including th. Bestandsnummer des Verkäufers 158878205
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Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -An Invitation for Actuaries to join this journey. While Deep Learning has shown remarkable success in the area of unstructured data like image classification, text analysis and speech recognition, there is very little literature on Deep Learning performed on structured/relational data. This investigation also focuses on applying Deep Learning on structured data because actuaries are more comfortable with structured data than unstructured data and so it can be a useful imitative step for other actuaries to apply Deep Learning to solve their own business problems.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 84 pp. Englisch. Bestandsnummer des Verkäufers 9783659961878
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Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. A Deep Learning Odessy | Syed Danish Ali (u. a.) | Taschenbuch | 84 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659961878 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 103016718
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