As I was going through some documentation on how to estimate the linear co-efficients (intercept and weights) here in this page (https://ml-cheatsheet.readthedocs.io/en/latest/linear_regression.html)
I could not understand the following statement:
There are two parameters (coefficients) in our cost function we can control: weight and bias . Since we need to consider the impact each one has on the final prediction, we use partial derivatives. To find the partial derivatives, we use the Chain rule. We need the chain rule because (−(+))2 is really 2 nested functions: the inner function −(+) and the outer function 2.
What I do not understand is which is the outer function that they define here as x2?