Python Deep Learning Cookbook

Implementing a single-layer neural network

Now we can move on to neural networks. We will start by implementing the simplest form of a neural network: a single-layer neural network. The difference from a perceptron is that the computations are done by multiple units (neurons), hence a network. As you may expect, adding more units will increase the number of problems that can be solved. The units perform their computations separately and are stacked in a layer; we call this layer the hidden layer. Therefore, we call the units stacked in this layer the hidden units. For now, we will only consider a single hidden layer. The output layer performs as a perceptron. This time, as input we have the hidden units in the hidden layer instead of the ...