Part I. Foundations of Transfer Learning -- Chapter 1. Introduction -- Chapter 2. From Machine Learning to Transfer Learning -- Chapter 3. Overview of Transfer Learning Algorithms -- Chapter 4. Instance Weighting Methods -- Chapter 5. Statistical Feature Transformation Methods -- Chapter 6. Geometrical Feature Transformation Methods -- Chapter 7. Theory, Evaluation, and Model Selection -- Part II. Modern Transfer Leaning -- Chapter 8. Pre-training and Fine-tuning -- Chapter 9. Deep Transfer Learning -- Chapter 10. Adversarial Transfer Learning -- Chapter 11. Generalization in Transfer Learning -- Chapter 12. Safe & Robust Transfer Learning -- Chapter 13. Transfer Learning in Complex Environments -- Chapter 14. Low-resource Learning -- Part III. Applications -- Chapter 15. Transfer Learning for Computer Vision -- Chapter 16. Transfer Learning for Natural language Processing -- Chapter 17. Transfer Learning for Speech Recognition -- Chapter 18. Transfer Learning for Activity Recognition -- Chapter 19. Federated Learning for Personalized Healthcare -- Chapter 20. Concluding Remarks.