Neural Networks are a means for classifying multi dimensional objects. We
concentrate on implementing back propagation networks with one hidden layer
as these networks have been covered by the 2006 NIPS map reduce paper
. Those networks are capable of learning not only linear separating hyper
planes but arbitrary decision boundaries.
Strategy for parallel backpropagation network
Design of implementation