Part I Foundations and methods 1. Object-oriented basis of artificial intelligence methodologies Kalidas Yeturu 2. Machine learning in physics and geometry Yang-Hui He, Elli Heyes, and Edward Hirst Part II Probability inspired models3. Learning and identity testing of Markov chains Geoffrey Wolfer and Aryeh Kontorovich 4. Data privacy for machine learning and statistics Vicenc¸ Torra 5. A Teacher-Student-based adaptive structural deep learning model and its estimating uncertainty of image data Takumi Ichimura, Shin Kamada, Toshihide Harada, and Ken Inoue Part III: Applications 6. Artificial intelligence in systems biology Abhijit Dasgupta and Rajat K. De 7. The calculated uncertainty of scientific discovery: From Maths to Deep Maths D. Douglas Miller 8. Indian courts of law can benefit immensely by adopting artificial intelligence methods in bail applications for speedy and accurate justice Arni S.R. Srinivasa Rao and Anil P. Gore