Train an SVM classifier with a linear kernel to classify the Churn variable. Evaluate the model

on a test set and report the accuracy.

$($b$)$ Split the data into training and test sets.

$($c$)$ Train an SVC model with a linear kernel.

$($d$)$ Make predictions on the test set and compute the accuracy.

$($e$)$ Repeat $($c$)$ and $($d$)$ but with a different type of kernel and compare the two models.

$($f$)$ Find and visualize the confusion matrices for the two models. Discuss the differences if any.