國立虎尾科技大學 |

Machine learning and data analytics for solving business problems = methods, applications, and case studies /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Machine learning and data analytics for solving business problems/ edited by Bader Alyoubi ... [et al.].
其他題名:	methods, applications, and case studies /
其他作者:	Alyoubi, Bader.
出版者:	Cham :Springer International Publishing : : 2022.,
面頁冊數:	xii, 206 p. :ill., digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Decision making - Data processing. -
電子資源:	https://doi.org/10.1007/978-3-031-18483-3
ISBN:	9783031184833

Machine learning and data analytics for solving business problems = methods, applications, and case studies /
Machine learning and data analytics for solving business problemsmethods, applications, and case studies /[electronic resource] :edited by Bader Alyoubi ... [et al.]. - Cham :Springer International Publishing :2022. - xii, 206 p. :ill., digital ;24 cm. - Unsupervised and semi-supervised learning,2522-8498. - Unsupervised and semi-supervised learning..

Introduction -- Supervised and unsupervised methods for customer segmentation -- Supervised and unsupervised methods for supply chain management -- Supervised and unsupervised methods for logistics improvement -- Design of recommender systems -- Supervised and unsupervised methods for e-marketing -- Analysis of Blockchain data -- Supervised and unsupervised methods applied in banking -- Cryptocurrency analysis -- Supervised and unsupervised methods to improve operational processes -- Big data analysis and summarization -- Intelligent Financial analysis and sales forecasting -- Financial data modeling and decision making -- Integration of learning methods in Smart ERP systems -- E-commerce recommender systems -- Social media and E-business analysis -- Intelligent Business control and monitoring systems -- Conclusion.

This book presents advances in business computing and data analytics by discussing recent and innovative machine learning methods that have been designed to support decision-making processes. These methods form the theoretical foundations of intelligent management systems, which allows for companies to understand the market environment, to improve the analysis of customer needs, to propose creative personalization of contents, and to design more effective business strategies, products, and services. This book gives an overview of recent methods - such as blockchain, big data, artificial intelligence, and cloud computing - so readers can rapidly explore them and their applications to solve common business challenges. The book aims to empower readers to leverage and develop creative supervised and unsupervised methods to solve business decision-making problems. Provides design and applications of machine learning and data analytics to solve business problems; Includes applications of supervised and unsupervised learning methods in intelligent management systems; Introduces case studies of business problems solved using innovative learning methods and data analytics techniques.

ISBN: 9783031184833

Standard No.: 10.1007/978-3-031-18483-3doiSubjects--Topical Terms:

568242
Decision making
--Data processing.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

Machine learning and data analytics for solving business problems = methods, applications, and case studies /
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520 $a This book presents advances in business computing and data analytics by discussing recent and innovative machine learning methods that have been designed to support decision-making processes. These methods form the theoretical foundations of intelligent management systems, which allows for companies to understand the market environment, to improve the analysis of customer needs, to propose creative personalization of contents, and to design more effective business strategies, products, and services. This book gives an overview of recent methods - such as blockchain, big data, artificial intelligence, and cloud computing - so readers can rapidly explore them and their applications to solve common business challenges. The book aims to empower readers to leverage and develop creative supervised and unsupervised methods to solve business decision-making problems. Provides design and applications of machine learning and data analytics to solve business problems; Includes applications of supervised and unsupervised learning methods in intelligent management systems; Introduces case studies of business problems solved using innovative learning methods and data analytics techniques.
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