neataptic
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Architecture-free neural network library with genetic algorithm implementations
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description: How to use the Perceptron network in Neataptic
authors: Thomas Wagenaar
keywords: feed-forward, neural-network, perceptron, MLP, architecture
This architecture allows you to create multilayer perceptrons, also known as feed-forward neural networks. They consist of a sequence of layers, each fully connected to the next one.

You have to provide a minimum of 3 layers (input, hidden and output), but you can use as many hidden layers as you wish. This is a `Perceptron` with 2 neurons in the input layer, 3 neurons in the hidden layer, and 1 neuron in the output layer:
```javascript
var myPerceptron = new architect.Perceptron(2,3,1);
```
And this is a deep multilayer perceptron with 2 neurons in the input layer, 4 hidden layers with 10 neurons each, and 1 neuron in the output layer
```javascript
var myPerceptron = new architect.Perceptron(2, 10, 10, 10, 10, 1);
```