Machine Learning By Sridhar Pdf -

[ y = w_0 + w_1 x_1 + w_2 x_2 + \dots + w_n x_n ]

[ J(w) = \frac{1}{2m} \sum_{i=1}^m (h_w(x^{(i)}) - y^{(i)})^2 ] machine learning by sridhar pdf

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 ): [ y = w_0 + w_1 x_1 +

[ w_j := w_j - \alpha \frac{\partial J(w)}{\partial w_j} ] machine learning by sridhar pdf

We minimize Mean Squared Error (MSE):

I notice you're asking about — but there's no widely known ML textbook by a single author "Sridhar" in standard academic or technical publishing (e.g., from Pearson, Wiley, O'Reilly, MIT Press, etc.).