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Machine Learning Approaches in Financial Analytics 2024th Edition (Intelligent Systems Reference Library, 254)
Author(s): Leandros A. Maglaras (Editor), Sonali Das (Editor), Naliniprava Tripathy (Editor), Srikanta Patnaik (Editor)
- Publisher: Springer
- Publication Date: August 28, 2024
- Edition: 2024th
- Language: English
- Print length: 503 pages
- ISBN-10: 3031610369
- ISBN-13: 978-3031610363
Book Description
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.
Editorial Reviews
Editorial Reviews
From the Back Cover
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.
