In this chapter, we walked through the convolutional layer on an example image. We tackled the practical aspects of understanding the convolutions. They can be convoluted but hopefully no longer confusing. We eventually applied this concept to a simple example in TensorFlow. We explored a common partner to convolutions, pooling layers. We explained the workings of max pooling layers, a common convolutional partner. Then, as we progressed, we put this into practice by adding a pooling layer to our example. We also practiced creating a max pooling layer in TensorFlow. We started adding convolutional neural nets to the font classification problem.
In the next chapter, we'll look at models with a time component, Recurrent Neural Networks (RNNs).
