Linear Regression and SGD

In class we covered the baseline stochastic gradient descent. Using the linear regression dataset from the class website, develop from scratch the baseline SGD algorithm that can estimate the L2-norm regularized model.

Clearly state the hyper-parameters you used and present the loss vs epoch plot that demonstrates the convergence of the algorithm and the final values of the parameters \(\mathbf w\) of the model.

You can generate the dataset with any number of examples \(m\) you need to demonstrate that the algorithm works.