This book highlights the evolution and interdisciplinary approach of AI and ML in image processing, tracing historical development and exploring their convergence with different fields. It delves into optimizing neural architectures and making deep learning models interpretable while exploring recent trends like versatile CNN applications and edge computing deployment. The intersection of AI and creativity, dynamic transfer learning, and domain adaptation are discussed alongside object detection techniques and reinforcement learning. It examines advanced applications in satellite imagery, healthcare, and smart cities, addressing ethical considerations like bias mitigation and transparency. This book also outlines future trends such as quantum-inspired computing and the evolution of edge AI ecosystems.