Frontmatter

Kapitel in diesem Buch

1. Frontmatter I
2. Preface V
3. Contents VII
4. List of authors IX
5. About the editors XIII
6. 1 Introduction to artificial intelligence 1
7. 2 AI technologies, tools, and industrial use cases 21
8. 3 Classification and regression algorithms 53
9. 4 Clustering and association algorithm 87
10. 5 Reinforcement learning 109
11. 6 Evaluation of AI model performance 125
12. 7 Methods of cross-validation and bootstrapping 145
13. 8 Meta-learning through ensemble approach: bagging, boosting, and random forest strategies 167
14. 9 AI: issues, concerns, and ethical considerations 189
15. 10 The future with AI and AI in action 213
16. 11 A survey of AI in industry: from basic concepts to industrial and business applications 233
17. 12 The intelligent implications of artificial intelligence-driven decision-making in business management 251
18. 13 An innovative analysis of AI-powered automation techniques for business management 269
19. 14 The smart and secured AI-powered strategies for optimizing processes in multi-vendor business applications 287
20. 15 Utilizing AI technologies to enhance e-commerce business operations 309
21. 16 Exploring the potential of artificial intelligence in wireless sensor networks 331
22. 17 Exploring artificial intelligence techniques for enhanced sentiment analysis through data mining 345
23. 18 Exploring the potential of artificial intelligence for automated sentiment 361
24. 19 A novel blockchain-based artificial intelligence application for healthcare automation 373
25. 20 Enhancing industrial efficiency with AI-enabled blockchain-based solutions 387
26. Index 401