Finally, we take part of our dataset and put it to one side. This is known as our test set and we will not touch it until after we have trained our model. This set is used to evaluate how well our trained model performs on new data that it hasn't seen before. There are many approaches to how you should split your data up into training and test sets, and we will go into detail about them all later in the book.

For now though, we'll do a simple 70:30 split, so we only use 70% of our total data to train our model and then test on the remaining 30%.