Partial Derivatives: Matrices and Local Extrema

This lecture covers the concept of hessian matrices for functions of several variables, defining them as the matrix of second partial derivatives. It explains the conditions for a hessian matrix to be symmetric and positive definite, leading to local extrema of a function. The demonstration involves the Taylor formula and the properties of positive definite matrices, showing how to determine local minima and maxima.