L w21 L w 21. J th th 1 2 th 2 2. We now have a formula to compute the gradient with respect to a certain weight.
We could simply use this formula to compute the gradient for all of the weights but that would involve a lot of redundant computation.
In an equation of a line we often want y by itself on one side of the equation. Main approach where the likelihood comes from The objective is to learn the underlying data distribution. X2 2x Dx Dx2 x2 Dx. In an equation of a line we often want y by itself on one side of the equation.