[ J(w) = \frac{1}{2m} \sum_{i=1}^m (h_w(x^{(i)}) - y^{(i)})^2 ]
[ y = w_0 + w_1 x_1 + w_2 x_2 + \dots + w_n x_n ] machine learning by sridhar pdf
We minimize Mean Squared Error (MSE):
Regression is a supervised learning technique used to predict continuous output variables. In linear regression, we assume a linear relationship between input features ( X ) and output ( y ): machine learning by sridhar pdf