Machine Learning and Data Analytics for Solving Business Problems

Methods, Applications, and Case Studies

Bader Alyoubi, Chiheb-Eddine Ben Ncir, Ibraheem Alharbi, Anis Jarboui (Herausgeber)

Buch | Hardcover

XII, 206 Seiten

2022 | 1st ed. 2022
Springer International Publishing (Verlag)
978-3-031-18482-6 (ISBN)

Artikel merken

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.

Bader Alyoubi is full Professor of Management Information Systems and Dean of the College of Business at the University of Jeddah, Saudi Arabia. His research interests include decision support systems and knowledge management methods and its application in business, government, and health domains. He is the author and co-author of more than 50 publications in the field of specialization. He established the Saudi Center for the Preparation and Empowerment of Entrepreneurs at the University of Jeddah. He has many contributions to the structuring of colleges and scientific disciplines at the University of Jeddah and Chairman of several committees.

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.

Erscheinungsdatum	17.12.2022
Reihe/Serie	Unsupervised and Semi-Supervised Learning
Zusatzinfo	XII, 206 p. 50 illus., 38 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Gewicht	488 g
Themenwelt	Technik ► Elektrotechnik / Energietechnik
Themenwelt	Technik ► Nachrichtentechnik
Schlagworte	Big Data • Blockchain data analysis • Cryptocurrencies analysis • data analytics • machine learning • Microfinance Analysis
ISBN-10	3-031-18482-3 / 3031184823
ISBN-13	978-3-031-18482-6 / 9783031184826
Zustand	Neuware