A neural network is a powerful data modeling tool that is able to capture and represent complex input/output relationships. Imagine the power of the machine which has the abilities of both computers and humans. It would be the most remarkable thing ever. A neural network usually involves a large number of processors operating in parallel, each with its own small sphere of knowledge and access to data in its local memory. The computing world has a lot to gain from neural networks. Their ability to learn by example makes them very flexible and powerful. They are also very well suited for real time systems because of their fast response and computational times which are due to their parallel architecture. With the correct implementation NN can be used naturally in online learning and large dataset applications. If the 21st Century is to be the age of intelligent machines, then 'Neural Networks' will become an integral part of life. This paper focuses on the many aspects of NN, the past, present and the future and explores what it has kept folded for us in the 'GENERATION NEXT…. . '

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Pattern Recognition Neuron Human Brain Supervised Learning Unsupervised Learning