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A multilayer perceptron (MLP) is a misnomer for a modern feedforward artificial neural network, consisting of fully connected neurons with a nonlinear kind of activation function, organized in at least three layers, notable for being able to distinguish data that is not linearly separable.[1] It is a misnomer because the original perceptron used a Heaviside step function, instead of a nonlinear kind of activation function (used by modern networks).
Modern feedforward networks are trained using the backpropagation method[2][3][4][5][6] and are colloquially referred to as the "vanilla" neural networks.[7]
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