The fields of Artificial Intelligence and Machine Learning have grown dramatically in recent years, with an increasingly impressive spectrum of successful applications. This book represents a key reference for anybody interested in the intersection between Mathematics and AI/ML and provides an overview of the current research streams.

Engineering Mathematics and Artificial Intelligence: Foundations, Methods, and Applications discusses the theory behind Machine Learning and shows how Mathematics can be used in Artificial Intelligence. The book illustrates how to improve existing algorithms by using advanced Mathematics and offers cutting-edge Artificial Intelligence technologies. The book goes on to discuss how Machine Learning can support mathematical modeling and how to simulate data by using artificial neural networks. Future integration between Machine Learning and complex mathematical techniques is also highlighted within the book.

This book is written for researchers, practitioners, engineers, and AI consultants.