The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, opti

A mathematical introduction to deep learning, written by a group of leading experts in the field.

Math for Deep Learning provides the essential math you need to understand deep learning discussions, explore more complex implementations, and better use the de

Math and Architectures of Deep Learning bridges the gap between theory and practice, laying out the math of deep learning side by side with practical implementa

An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and res