From the course: Deep Learning: Getting Started
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Hidden layers
From the course: Deep Learning: Getting Started
Hidden layers
- Hidden layers in a neural network form the brain where knowledge is acquired and used. An ANN can have one or more hidden layers. The more the number of layers, the deeper the network is. Each hidden layer can have one or more nodes. Typically node count is configured in the range of 2 power n Example counts may be 8, 16, 32, 64, 128, et cetera. A neural networks architecture is defined by the number of layers and nodes in that layer. How are the inputs and outputs connected? The output of each node in the previous layer will become the input for every node in the current layer. Similarly, the output of each node in the current layer is passed to every node in the next layer. In the example shown, there are four nodes in the first hidden layer, producing four outputs from their activation functions. There are five nodes in the second layer. The four outputs from the first layer are passed to each of the five nodes in the second layer. How do we determine the right number of layers…
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