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This article delves into the intersection of deep learning and mathematics, shedding light on the profound relationship between these two fields. Deep learning, a subfield of artificial intelligence, has revolutionized various domains, but its foundations are deeply rooted in mathematical principles. This paper explores the mathematical underpinnings of deep learning algorithms, such as linear algebra, calculus, probability theory, and optimization. Additionally, it examines how mathematics plays a crucial role in understanding, developing, and advancing deep learning techniques. By highlighting key concepts, applications, and case studies, this article aims to emphasize the interplay between deep learning and mathematics, paving the way for further exploration and innovation in this exciting frontier.