Self Organizing Map is one of the most popular neural network models. It belongs to the category of competitive learning networks. It is based on unsupervised learning, which means that no human intervention is needed during the learning and that little needs to be known about the characteristics of the input data. Self Organizing Map also describes a mapping from a higher-dimensional input space to a lower dimensional map space. The procedure for placing a vector from data space onto the map is to find the node with the closest weight vector to the data space vector.