This book offers a focused collection of lectures and tutorials on applying machine learning techniques to research in theoretical physics and pure mathematics. Machine learning continues to transform the scientific landscape, providing powerful tools capable of driving significant advances across these disciplines. Through clear conceptual explanations and practical examples, this text equips students and researchers with the knowledge and skills needed to integrate these methods into the...

This book introduces several novel contributions into the current literature. Firstly, given that microgrid topologies are paramount in theoretical analysis, the author has proposed a rigorous method of computing the network’s admittance matrix and developed to facilitate the stability analysis of DC microgrids supplying nonlinear loads. This unique approach enabled the factorisation of the admittance matrix in a particular way that facilitates a rigorous theoretical analysis for deriving ...