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Mathematics for Machine Learning by Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong is a foundational text designed to bridge the gap between mathematical theory and practical machine learning applications. The book introduces core mathematical concepts such as linear algebra, analytic geometry, matrix decompositions, vector calculus, probability theory, and optimization — all within the context of machine learning.