Feedforward Neural Network (FNN) is a biologically inspired classification algorithm. It consists of a (possibly large) number of simple neuronlike processing units, organized in layers. Every unit in a layer is connected with units in the previous layer. These connections are not all equal: each connection may have a different strength or weight. The weights on these connections encode the knowledge of a network. Often the units in a neural network are also called nodes. Data enters at the inputs and passes through the network, layer by layer until it arrives at the outputs. During normal operation, that is when it acts as a classifier, there is no feedback between layers. This is why they are called feedforward neural networks.
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