ABSTRACT
This chapter explains neural networks as a broad class of models that mimic functioning inside the human brain and are known as biological neurons. Neural networks are very sophisticated modeling techniques capable of modeling extremely complex functions. In particular, neural networks are nonlinear. Linear modeling has been the commonly used technique in most modeling domains since linear models have well-known optimization strategies. Neural networks keep in check the curse of dimensionality problem that bedevils attempts to model nonlinear functions with large numbers of variables. The neural network user gathers representative data, and then invokes training algorithms to automatically learn the structure of the data. The biological neuron is the most important functional unit in human brain and is a class of cells called as NEURON. Artificial Neural Networks consists of many simple elements called neurons. The neurons interact with each other using weighted connection similar to biological neurons.
