Exercise -2 (Machine Learning) Answer the following questions. (10-15 points) a). What is formal learning and explain the different stages involved? b). Explain Probably Approximately Correct in detail. c). Explain Simple Linear Regression with an example. Give the equations for squared loss, Mean Squared Error, and the cost function. d). What is a Convex Function? Explain in detail what is Gradient Descent. Give the convergence algorithm and discuss the gradient descent optimization. e). Explain Logistic Regression with an example. Derive the cost function from sigmoid to log loss.