Neural networks, also conventionally known as connectionist models, are inspired by the human brain. Like the human brain, neural networks are a collection of a large number of artificial neurons connected to each other via synaptic strengths called weights. Just as we learn through examples provided to us by our elders, artificial neural networks learn by examples presented to them as training datasets. With a sufficient number of training datasets, artificial neural networks can generalize the information and can then be employed for unseen data as well. Awesome, they sound like magic!
Neural networks are not new; the first neural network model, McCulloch Pitts (MCP) (http://vordenker.de/ggphilosophy/mcculloch_a-logical-calculus.pdf ...
