Homework $6$: Support Vector Machines

In this assignment we'll explore the details of the Soft$-$Margin SVM and look at how the choice of tuning parameters affects the learned models. We'll also look at kernel SVMs for non$-$linearly separable and methods for choosing and visualizing good hyperparameters.

Note: Below are some helper functions which are used throughout this notebook. Execute these before continuing. Do not modify.