In the previous chapter, we learned all about dense neural networks.
In this chapter, we're going to move on to a more recent technique: the convolutional neural network. This is an approach that you can use to process a wide array of images, and you'll find that, as we show you how it works, it's actually much more accurate and effective than the classical neural network.
In this section, we're going to learn all about convolutions and how to apply them to images, and then we're going to learn about another operation known as pooling. Armed with these two new techniques, we're going to build an actual convolutional neural network and train it in our MNIST digits, which will reveal that it's much more accurate. Finally, we're going to build an actual deep network. The idea behind deep learning is that you take...
