This book explains how AI and Machine Learning can be applied to help businesses solve problems, support critical thinking and ultimately create customer value and increase profit.
By considering business strategies, business process modeling, quality assurance, cybersecurity, governance and big data and focusing on functions, processes, and people's behaviors it helps businesses take a truly holistic approach to business optimization. It contains practical examples that make it easy to understand the concepts and apply them.
It is written for practitioners (consultants, senior executives, decision-makers) dealing with real-life business problems on a daily basis, who are keen to develop systematic strategies for the application of AI/ML/BD technologies to business automation and optimization, as well as researchers who want to explore the industrial applications of AI and higher-level students.
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für Beruf und Forschung
Academic, Professional, and Professional Practice & Development
Illustrationen
60 s/w Abbildungen, 60 s/w Zeichnungen, 21 s/w Tabellen
21 Tables, black and white; 60 Line drawings, black and white; 60 Illustrations, black and white
Maße
Höhe: 234 mm
Breite: 156 mm
Dicke: 18 mm
Gewicht
ISBN-13
978-1-032-02886-6 (9781032028866)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Autor*in
University of South Florida
Foreword by Andy Lyman. Preface. Readers. Figures. Acknowledgments. Authors. 1 Artificial intelligence and machine learning: Opportunities for digital business. 2 Data to decisions: Evolving interrelationships. 3 Digital leadership: Strategies for AI adoption. 4 Machine learning types: Statistical understanding in the business context. 5 Dynamicity in learning: Smart selection of learning techniques. 6 Intelligent business processes with embedded analytics. 7 Adopting data-driven culture: Leadership and change management for business optimization. 8 Quality and risks: Assurance and control in BO. 9 Cybersecurity in BO: Significance and challenges for digital business. 10 Natural intelligence and social aspects of AI-based decisions. 11 Investing in the future technology of self-driving vehicles: Case study. Appendix A: Frameworks and libraries for ML. Appendix B: Datasets for ML and predictive analytics. Appendix C: AI and BO research areas. Index.
