Each node in the newok has one or more inputs and an output. Each input has an associated weight and the node has a bias value. The value of each input multiplies its weight. Product value if inputs are summed up and the bias is added to the result. The result is input to a function represented by the node to generate the output value. The function maps the sum to an output value.
Training the network is to find the set of weights and boss’s that generate the least error. This is done by using the gradient descend algorithm.
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