Use these additional exercises to assist in your learning and test your knowledge further.  

Answer the following questions:

1. Name three different activation functions. Remember, Google is your friend.
2. What is the purpose of a bias?
3. What would you expect to happen if you reduced the number of epochs in one of the chapter samples? Did you try it?
4. What is the purpose of backpropagation?
5. Explain the purpose of the Cost function.
6. What happens when you increase or decrease the number of encoding dimensions in the Keras autoencoder example?
7. What is the name of the layer type that we feed input into?
8. What happens when you increase or decrease the batch size?
9. What is the shape of the input Tensor for the Keras example? Hint: we already have a print statement displaying this.
10. In the last exercise, how many MNIST samples do we train and test with?

As we progress in the book, the additional exercises will certainly become more difficult. For now, though, take some time to answer the questions and test your knowledge.