Introducing Convolution Neural Networks
In this section, you will learn about CNNs. Specifically, you will first get an understanding of the sort of operations present in a CNN, such as convolution layers, pooling layers, and fully connected layers. Next, we will briefly see how all of these are connected to form an end-to-end model. Then we will dive into the details of each of these operations, define them mathematically, and learn how the various hyperparameters involved with these operations change the output produced by them.
CNN fundamentals
Now, let's explore the fundamental idea behind a CNN without delving into too much technical detail. As noted in the preceding paragraph, a CNN is a stack of layers, such as convolution layers, pooling layers, and fully connected layers. We will discuss each of these to understand their role in the CNN.
Initially, the input is connected to a set of convolution layers. These convolution layers slide a patch of weights (sometimes called the convolution...
