Machine Learning Approaches in Financial Analytics (eBook)

Artikelnummer: 978-3-031-61037-0
Einband: PDF
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This book addresses the growing need for a comprehensive guide to the application of machine learning in financial analytics. It offers a valuable resource for both beginners and experienced professionals in finance and data science by covering the theoretical foundations, practical implementations, ethical considerations, and future trends in the field. It bridges the gap between theory and practice, providing readers with the tools and knowledge they need to leverage the power of machine learning in the financial sector responsibly.


accessibilitysupport@springernature.com

This book addresses the growing need for a comprehensive guide to the application of machine learning in financial analytics. It offers a valuable resource for both beginners and experienced professionals in finance and data science by covering the theoretical foundations, practical implementations, ethical considerations, and future trends in the field. It bridges the gap between theory and practice, providing readers with the tools and knowledge they need to leverage the power of machine learning in the financial sector responsibly.


accessibilitysupport@springernature.com
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VerlagSpringer Nature Switzerland
EinbandPDF
Erscheinungsjahr2024
Seitenangabe483 S.
AusgabekennzeichenEnglisch
AbbildungenXX, 483 p. 105 illus., 88 illus. in color.
Masse18'790 KB
PlattformPDF
ReiheIntelligent Systems Reference Library; Intelligent Technologies and Robotics; Intelligent Technologies and Robotics
AutorMaglaras, Leandros A. (Hrsg.) / Das, Sonali (Hrsg.) / Tripathy, Naliniprava (Hrsg.) / Patnaik, Srikanta (Hrsg.)

Alle Bände der Reihe "Intelligent Systems Reference Library; Intelligent Technologies and Robotics; Intelligent Technologies and Robotics (R0)"

Weitere Titel von Leandros A. (Hrsg.) Maglaras

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