Math 2.0

concept

Gradient

Summary

Let ff be a differentiable real-valued function on an open subset of Rn\mathbb{R}^n. Its gradient at a point aa is the vector ∇f(a)\nabla f(a) of its partial derivatives at aa. It points in the direction in which ff increases fastest, and its length is that fastest rate of increase. The derivative of ff at aa is the dot product with the gradient: Df(a)(v)=∇f(a)⋅vDf(a)(v) = \nabla f(a) \cdot v.

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  • edge specializes both: the more general notions and the special cases (0 of 1)

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Sources

  1. Web https://en.wikipedia.org/wiki/Gradient, lead section