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Lingua: Inglese
Editore: Engineering Science Reference, 2023
ISBN 10: 1668444844 ISBN 13: 9781668444849
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents research on the roles of artificial intelligence and machine learning algorithms in financial sectors with special reference to complex financial applications such as financial risk management in big data environments. The book also addresses broad.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Advanced Machine Learning Algorithms for Complex Financial Applications | Mohammad Irfan (u. a.) | Taschenbuch | Kartoniert / Broschiert | Englisch | 2023 | IGI Global | EAN 9781668444849 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Da: AHA-BUCH GmbH, Einbeck, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The advancements in artificial intelligence and machine learning have significantly affected the way financial services are offered and adopted today. Important financial decisions such as investment decision making, macroeconomic analysis, and credit evaluation are becoming more complex within the field of finance. Artificial intelligence and machine learning, with their spectacular success accompanied by unprecedented accuracies, have become increasingly important in the finance world. Advanced Machine Learning Algorithms for Complex Financial Applications provides innovative research on the roles of artificial intelligence and machine learning algorithms in financial sectors with special reference to complex financial applications such as financial risk management in big data environments. In addition, the book addresses broad challenges in both theoretical and application aspects of artificial intelligence in the field of finance. Covering essential topics such as secure transactions, financial monitoring, and data modeling, this reference work is crucial for financial specialists, researchers, academicians, scholars, practitioners, instructors, and students.