Buch, Englisch, 324 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 458 g
Research and Applications
Buch, Englisch, 324 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 458 g
ISBN: 978-1-032-02886-6
Verlag: CRC Press
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.
Zielgruppe
Academic, Professional, and Professional Practice & Development
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Technik Allgemein Mess- und Automatisierungstechnik
- Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
- Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering
- Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Office Management, Büroorganisation
- Wirtschaftswissenschaften Betriebswirtschaft Management Wissensmanagement
- Mathematik | Informatik EDV | Informatik Business Application Unternehmenssoftware
- Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Wirtschaftswissenschaften Betriebswirtschaft Management Unternehmensorganisation & Entwicklungsstrategien
Weitere Infos & Material
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.
