Multivariate calculus from first principles
The gradient packaged all the first derivatives. The Hessian packages all the second derivatives of a scalar function f: Rⁿ → R into a matrix. Where the gradient gives slope, the Hessian gives curvature: how the slope itself changes as you move around.
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▶ The Hessian