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.