Linear Regression, Gradient Descent, Machine Learning, Mathematics, Data Analysis.
θ0) w.r.t θ1, is nearly identical for most of the process, as there is no partial derivatives dealt with. The only small difference is in differentiating the second product of the chain rule, but it introduced no need for new laws or formulas. Why is this true? After the intimidation subsides,