A neural network model is similar to the preceding logistic regression model. The only difference is the addition of hidden layers between the input and output layers. Let's consider a single hidden layer neural network for classification to understand the process as shown in the following diagram:
Here, Layer 0 is the input layer, Layer 1 is the hidden layer, and Layer 2 is the output layer. This is also known as two layered neural networks, owing to the fact that when we count the number of layers in a neural network, we don't consider input layer as the first layer. Thus, input layer is considered as Layer 0 and ...
