This textbook introduces linear algebra and optimization in the context of machine learning. Examples and exercises are provided throughout the book. A solution
Volume 2 applies the linear algebra concepts presented in Volume 1 to optimization problems which frequently occur throughout machine learning. This book blends
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, opti
An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay betw
Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes