Mathematics for Machine Learning and AI provides a foundational and practical understanding of the core mathematical concepts that underpin modern artificial intelligence systems. It covers essential topics such as linear algebra, calculus, probability theory, statistics, optimization, and discrete mathematics, all tailored to their applications in machine learning and AI. This book bridges the gap between mathematical theory and practical implementation, making complex topics accessible through clear explanations, real-world examples, and hands-on problem-solving. Readers will learn how...