Probabilistic methods for financial and marketing informatics Nepolitan, Richard E.

By:

Nepolitan, Richard E

Contributor(s):

Jiang, Xia

Publication details: San Francisco Morgan Kaufmann 2007Description: x, 413 pISBN:

9780123704771

Subject(s):

DDC classification:

332.01519542

Summary: This book is for all RandD 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 is in advertising, venture capital decision making, operational risk measurement in any industry, credit scoring, and investment science. (Source: http://www.elsevier.com)

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Holdings
Item type	Current library	Call number	Status	Date due	Barcode	Item holds
Book	Ahmedabad	332.01519542 N3P7 (Browse shelf(Opens below))	Available		167983

Total holds: 0

Includes bibliographical references (p. 397-408) and index.

This book is for all RandD 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 is in advertising, venture capital decision making, operational risk measurement in any industry, credit scoring, and investment science. (Source: http://www.elsevier.com)

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