Simple Linear Regression, Regression Cost Function, Cost Function, Machine Learning.
the best-fit line so that we can get the summation of all the specific errors and it should be minimal. So that is why we are taking this cost function in this specific way. hθ(x)^i is my predicted point. And y^i is my truth point/true output. When we do the subtraction we can get the error value