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Perceptrons are the simplest form of Neural Nets. The learning process involves changing the weights by an amount proportional to the difference between the desired output and the actual output. This example demonstrates a Network of two Neurons learning to classify marked dataset.

Each Neuron generates a decision boundary represented by a line.