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Partial Derivatives and Gradients

Explore the concept of partial derivatives and gradients for multivariate functions in this lesson. Learn how to compute gradients using Python tools such as NumPy and SciPy, understand their role in indicating the direction of steepest ascent, and visualize these concepts to grasp the impact of variable changes on function values.

What are gradients?

A multivariate function in mathematics is a function that takes more than one input variable and produces one or more output variables. For example, the volume of a cylinder f(x,y)=πx2yf(x, y) = \pi x^2y is a multivariate function because it takes two inputs: the radius xx and the height yy of the cylinder.

For multivariate functions f(x)=f(x1,x2,...,xm)f(x) = f(x_1, x_2, ..., x_m)where the input xRmx \in \R^m ...