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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.