A Three-Layer Example: Working on the Hidden Layer
Explore how to compute the output of the hidden layer in a three-layer neural network by applying the sigmoid activation function. Understand the process of moderating inputs with weights and passing signals through each layer, which remains consistent regardless of the number of layers in the network.
We'll cover the following...
We'll cover the following...
Output of the hidden layer
Let’s visualize the combined moderated inputs into the second hidden layer.
So far, so good, but there’s more to do. We remember those nodes apply a sigmoid activation function to make the response to the signal more like those found in nature. So let’s do that:
The sigmoid function is applied to each element in to produce the matrix, which has the output of the middle hidden layer:
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