Max/min: optimization

Related lectures (29)

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Explains how to find local extrema of functions using derivatives and critical points.

Discusses local extrema of functions in two variables around the point (0,0).

Covers the method of Lagrange multipliers to find extrema subject to constraints.

Covers the concepts of optimization, focusing on finding maximum and minimum values.

Covers the concepts of limits and continuity, focusing on the demonstration of various theorems.

Covers Taylor's formula, developments, and extrema of functions, discussing convexity and concavity.

Explores the conditions for local extrema of functions in several variables, including critical points and the Hessian matrix.

Covers the optimization of functions, focusing on finding the maximum and minimum values over a given domain.

Explores real functions, covering parity, periodicity, and polynomial functions.

Explains extrema of functions in several variables, stationary points, saddle points, and the role of the Hessian matrix.