Advanced Explorations in Machine Learning, Computer Vision, and IoT focuses on the convergence of machine learning algorithms, computer vision techniques, and Internet of Things (IoT) infrastructures to enable scalable, adaptive, and real-time intelligent applications. Balancing strong theoretical foundations with system-level design considerations, the book serves as a structured guide for readers interested in how advanced mathematical models and learning paradigms drive modern AI-enabled IoT ecosystems. The book begins with the mathematical, probabilistic, and computational principles underlying machine learning and visual intelligence, with subsequent chapters exploring linear and nonlinear models, kernel methods, neural networks, deep learning architectures, and optimisation techniques.