Linear Regression with Closed form solutions
Key moments in this video
00:12 RECAP – Linear Regression and Least squares loss
00:50 Write the loss function in matrix notation: L(w)=〖(y-Xw)〗^T (y-Xw)
01:47 Solving this the optimal set of weights is obtained as: w^*=〖(X^T X)〗^(-1) X^T y
02:36 Example
Link to Linear Regression with Gradient descent
• Linear Regression with Gradient descent