Isbn: 9780123704771 - probabilistic methods for financial and marketing informatics (3 resultados)

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  • Idioma: Inglés

    Editorial: Morgan Kaufmann, 2007

    0123704774 / 9780123704771

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    Librería: Recycle Bookstore, San Jose, CA, Estados Unidos de AmericaRecycle Bookstore

    Vendedor de 4 estrellas
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    Condición: Usado - Bueno

    EUR 55,05

    Envío por EUR 5,13 
    Se envía dentro de Estados Unidos de America

    Cantidad disponible: 1 disponible

    Hardcover. Condición: Very Good. Book has light rubbing to covers, light wear to edges, small bends and faint scuffs to corners. otherwise in great condition, strong binding, clean and unmarked pages; an overall sturdy, handsome copy.

  • Idioma: Inglés

    Editorial: Elsevier Science Mär 2007, 2007

    0123704774 / 9780123704771

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    • Impresión bajo demanda

    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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    Condición: Nuevo

    EUR 68,95

    Envío por EUR 23,00 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 2 disponibles

    Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Probabilistic Methods for Financial and Marketing Informatics aims to provide students with insights and a guide explaining how to apply probabilistic reasoning to business problems. Rather than dwelling on rigor, algorithms, and proofs of theorems, the authors concentrate on showing examples and using the software package Netica to represent and solve problems. The book contains unique coverage of probabilistic reasoning topics applied to business problems, including marketing, banking, operations management, and finance. It shares insights about when and why probabilistic methods can and cannot be used effectively. This book is recommended for all R&D professionals and students who are involved with industrial informatics, that is, applying the methodologies of computer science and engineering to business or industry information. This includes computer science and other professionals in the data management and data mining field whose interests are business and marketing information in general, and who want to apply AI and probabilistic methods to their problems in order to better predict how well a product or service will do in a particular market, for instance. Typical fields where this technology is used are in advertising, venture capital decision making, operational risk measurement in any industry, credit scoring, and investment science. 432 pp. Englisch.…

  • Idioma: Inglés

    Editorial: Elsevier Science, 2007

    0123704774 / 9780123704771

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    • Impresión bajo demanda

    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

    Vendedor de 5 estrellas
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    Condición: Nuevo

    EUR 73,12

    Envío por EUR 35,00 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 2 disponibles

    Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Probabilistic Methods for Financial and Marketing Informatics aims to provide students with insights and a guide explaining how to apply probabilistic reasoning to business problems. Rather than dwelling on rigor, algorithms, and proofs of theorems, the authors concentrate on showing examples and using the software package Netica to represent and solve problems. The book contains unique coverage of probabilistic reasoning topics applied to business problems, including marketing, banking, operations management, and finance. It shares insights about when and why probabilistic methods can and cannot be used effectively. This book is recommended for all R&D professionals and students who are involved with industrial informatics, that is, applying the methodologies of computer science and engineering to business or industry information. This includes computer science and other professionals in the data management and data mining field whose interests are business and marketing information in general, and who want to apply AI and probabilistic methods to their problems in order to better predict how well a product or service will do in a particular market, for instance. Typical fields where this technology is used are in advertising, venture capital decision making, operational risk measurement in any industry, credit scoring, and investment science. …