Multivariate calculus from first principles
When the output is a vector too, a function f: Rⁿ → Rᵐ, one gradient isn't enough. You need the partial of every output with respect to every input. Stack them all into a matrix and you get the Jacobian J, the full first derivative of a vector-valued map.
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▶ The Jacobian