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A multilayer perceptron is a kind of feed forward artificial neural network, which is a mathematic model inspired by the biological neural network. The multilayer perceptron can be used for various machine learning tasks such as classification and regression.
Here is an example multilayer perceptron:
https://docs.google.com/drawings/d/1DCsL5UiT6eqglZDaVS1Ur0uqQyNiXbZDAbDWtiSPWX8/pub?w=813&h=368
The basic component of a multilayer perceptron is the neuron. A typical In a multilayer perceptron, the neurons are aligned in layers and in any two adjacent layers the neurons are connected in pairs with weighted edges. A practical multilayer perceptron consists of at least two three layers of neurons, including one input layer, zero one or more hidden layers, and one output layers.
Here is an example multilayer perceptron with 1 input layer, 1 hidden layer and 1 output layer:
https://docs.google.com/drawings/d/1DCsL5UiT6eqglZDaVS1Ur0uqQyNiXbZDAbDWtiSPWX8/pub?w=813&h=368
How Multilayer Perceptron works?
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