For a linear regression model, the following data is obtained. x -1.34 -0.45 0.45 1.34 where Ypred = WTx + b is the prediction model. 1. Initialize W = 0.1, b = 0.2, Take learning rate a = 0.01 and apply Gradient Descent algorithm (for one single iteration) to obtain the next value of W = ? and b = ?, y 2 4 6 8 Y pred 0.08 1.02 1.95 2.89 2. Determine Mean Square Error (MSE) for the data given in the table.

For a linear regression model, the following data is obtained. x -1.34 -0.45 0.45 1.34 where Ypred = WTx + b is the prediction model. 1. Initialize W = 0.1, b = 0.2, Take learning rate a = 0.01 and apply Gradient Descent algorithm (for one single iteration) to obtain the next value of W = ? and b = ?, y 2 4 6 8 Y pred 0.08 1.02 1.95 2.89 2. Determine Mean Square Error (MSE) for the data given in the table.