Gradient Descent, Linear Regression, Machine Learning.
that ()² is an outside function that contains y-(mx+b). Now, let’s break down each step according to the chain rule: Take a derivative of an outside function: ()² becomes 2() Keep an inside function as-is: y-(mx+b) Take a partial derivative with respect to m: 0-(x+0) or -x. Lets elaborate on how we