Directional derivatives (going deeper) (article) | Khan Academy
https://www.khanacademy.org/math/multivariable-calculus/multivariable-derivatives/partial-derivative-and-gradient-articles/a/directional-derivatives-going-deeper
WEBComputing the directional derivative involves a dot product between the gradient ∇ f and the vector v → . For example, in two dimensions, here's what this would look like: ∇ v → f ( x, y) = ∇ f ⋅ v → = [ ∂ f ∂ x ∂ f ∂ y] ⋅ [ v 1 v 2] = v 1 ∂ f ∂ x ( x, y) + v 2 ∂ f ∂ y ( x, y) Here, v 1 and v 2 are the components of v → . v → = [ v 1 v 2]
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