书目名称 | Novel Financial Applications of Machine Learning and Deep Learning | 副标题 | Algorithms, Product | 编辑 | Mohammad Zoynul Abedin,Petr Hajek | 视频video | | 概述 | Includes a wide range of machine learning algorithms covering a variety of tasks in financial applications.Focuses on financial product modeling.Provides advanced knowledge on classifier hybridization | 丛书名称 | International Series in Operations Research & Management Science | 图书封面 |  | 描述 | .This book presents the state-of-the-art applications of machine learning in the finance domain with a focus on financial product modeling, which aims to advance the model performance and minimize risk and uncertainty. It provides both practical and managerial implications of financial and managerial decision support systems which capture a broad range of financial data traits. It also serves as a guide for the implementation of risk-adjusted financial product pricing systems, while adding a significant supplement to the financial literacy of the investigated study...The book covers advanced machine learning techniques, such as Support Vector Machine, Neural Networks, Random Forest, .K.-Nearest Neighbors, Extreme Learning Machine, Deep Learning Approaches, and their application to finance datasets. It also leverages real-world financial instances to practice business product modeling and data analysis. Software code, such as MATLAB, Python and/or R including datasets within a broad range of financial domain are included for more rigorous practice...The book primarily aims at providing graduate students and researchers with a roadmap for financial data analysis. It is also intended | 出版日期 | Book 2023 | 关键词 | Financial Applications; Machine Learning; Deep Learning; Algorithms; Product Modeling | 版次 | 1 | doi | https://doi.org/10.1007/978-3-031-18552-6 | isbn_softcover | 978-3-031-18554-0 | isbn_ebook | 978-3-031-18552-6Series ISSN 0884-8289 Series E-ISSN 2214-7934 | issn_series | 0884-8289 | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
The information of publication is updating
|
|