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Machine learning and data analytics for solving business problems [electronic resource] : methods, applications, and case studies / Bader Alyoubi, Chiheb-Eddine Ben Ncir, Ibraheem Alharbi, Anis Jarboui, editors.

Alyoubi, Bader.; Ben N'Cir, Chiheb-Eddine.; Alharbi, Ibraheem.; Jarboui, Anis.
2022
Q325.5
Available Online
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Title
Machine learning and data analytics for solving business problems [electronic resource] : methods, applications, and case studies / Bader Alyoubi, Chiheb-Eddine Ben Ncir, Ibraheem Alharbi, Anis Jarboui, editors.
ISBN
9783031184833 (electronic bk.)
3031184831 (electronic bk.)
3031184823
9783031184826
DOI
https://doi.org/10.1007/978-3-031-18483-3
Published
Cham : Springer, 2022.
Language
English
Description
1 online resource (214 pages).
Item Number
10.1007/978-3-031-18483-3 doi
Call Number
Q325.5
Dewey Decimal Classification
006.3/1
Summary
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.
Note
Includes index.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed January 5, 2023).
Added Author
Alyoubi, Bader.
Ben N'Cir, Chiheb-Eddine.
Alharbi, Ibraheem.
Jarboui, Anis.
Series
Unsupervised and semi-supervised learning.
Available in Other Form
Machine Learning and Data Analytics for Solving Business Problems
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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.

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