The Essentials of Machine Learning in Finance and Accounting

The Essentials of Machine Learning in Finance and Accounting - Paperback

$89.08
Sale price  $89.08 Regular price 
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The Essentials of Machine Learning in Finance and Accounting

The Essentials of Machine Learning in Finance and Accounting - Paperback

$89.08
Sale price  $89.08 Regular price 

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by Mohammad Zoynul Abedin (Editor), M. Kabir Hassan (Editor), Petr Hajek (Editor)

This book introduces machine learning in finance and illustrates how to integrate computational tools with numerical finance with real world applications.

Author Biography

Mohammad Zoynul Abedin is an associate professor of Finance at the Hajee Mohammad Danesh Science and Technology University, Bangladesh. Dr. Abedin continuously publishes academic papers in refereed journals. Moreover, Dr. Abedin served as an ad hoc reviewer for many academic journals. His research interest includes data analytics and business intelligence.

M. Kabir Hassan is a professor of Finance at the University of New Orleans, USA. Prof. Hassan has over 350 papers (225 SCOPUS, 108 SSCI, 58 ESCI, 227 ABDC, 161 ABS) published as book chapters and in top refereed academic journals. According to an article published in Journal of Finance, the number of publications would put Prof. Hassan in the top 1% of peers who continue to publish one refereed article per year over a long period of time.

Petr Hajek is currently an associate professor with the Institute of System Engineering and Informatics, University of Pardubice, Czech Republic. He is the author or co-author of four books and more than 60 articles in leading journals. His current research interests include business decision making, soft computing, text mining, and knowledge-based systems.

Mohammed Mohi Uddin is an assistant professor of Accounting at the University of Illinois Springfield, USA. His primary research interests concern accountability, performance management, corporate social responsibility, and accounting data analytics. Dr. Uddin published scholarly articles in reputable academic and practitioners' journals.

Number of Pages: 234
Dimensions: 0.6 x 9.6 x 6.9 IN
Illustrated: Yes
Publication Date: June 21, 2021

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