4 Neural Network LayersEach layer receives its inputs from the previous layer and forwards its outputs to the next layer
5 Multilayer feed forward network It contains one or more hidden layers (hidden neurons).“Hidden” refers to the part of the neural network is not seen directly from either input or output of the network .The function of hidden neuron is to intervene between input and output.By adding one or more hidden layers, the network is able to extract higher- order statistics from input
6 Neural Network Learning Back-Propagation Algorithm:function BACK-PROP-LEARNING(examples, network) returns a neural networkinputs: examples, a set of examples, each with input vector x and output vector ynetwork, a multilayer network with L layers, weights Wj,i , activation function grepeatfor each e in examples dofor each node j in the input layer do aj ‰ xj[e]for l = 2 to M doini ‰ åj Wj,i ajai ‰ g(ini)for each node i in the output layer doDj ‰ g’(inj) åi Wji Difor l = M – 1 to 1 dofor each node j in layer l doDj ‰ g’(inj) åi Wj,i Difor each node i in layer l + 1 doWj,i ‰ Wj,i + a x aj x Diuntil some stopping criterion is satisfiedreturn NEURAL-NET-HYPOTHESIS(network)[Russell, Norvig] Fig Pg. 746
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