In a series of a few blog posts, I will present classical and non-classical results on symmetric positive definite matrices. Beyond being mathematically exciting, they arise naturally a lot in machine learning and optimization, as Hessians of twice continuously differentiable convex functions and through kernel methods. In this post, I will focus on the benefits…