00:01
Hi, i'm david and i'm here to help you answer your question.
00:03
Now let me bring up your question here.
00:06
In this question here, we want to discuss about the dorsional derivative.
00:11
Let me remind you that the ddural derivative denoted by the d, f, and then under the vector u, which is equal to the gradient of the f, and the point x0, y, 0, and c0, dot with the unit factor u.
00:29
So the vector yield will be over the node under you.
00:34
So in this question here, we've given the function f xy, it will equal to the x power y.
00:43
And then from here, we need to find the gradient of the f.
00:48
So the gradient of the f just equal to the f first partial derivative respect to the x and partially relative to respect to the y.
00:55
And then it will do the derivative respect to the x, it will be just equal to x will be the random variable and y will be the constant.
01:04
So this one just equal to the y, x power, y minus 1...