Exercises

Now that we have finished the first chapter in this exciting journey, I've got a challenge for you! You'll find some exercises that you can do that are all themed around what we've covered in this chapter!

So, why not try to do the following:

1. Expand the two-layer neural network in Python to three layers.
2. Within the GitHub repository, you will find an Excel file called 1 Excel Exercise. The goal is to classify three types of wine by their cultivar data. Build a logistic regressor to this end in Excel.
3. Build a two-layer neural network in Excel.
4. Play around with the hidden layer size and learning rate of the 2-layer neural network. Which options offer the lowest loss? Does the lowest loss also capture the true relationship?