Neural Networks: The Machine Brain

Our brain is made up of billions of nerve cells, called neurons. Arranged in a network, neurons communicate with each other in a sequence-like manner: Once one neuron receives information, it passes it to another neuron, which passes it to another and so on. Neurons can even signal several neighboring neurons at once. For example, one neuron might transmit information about the location of a baseball pitch that’s flying toward you while other neurons alert your muscles to get ready to swing the bat.This interconnected system allows us to constantly accumulate new information as the more familiar we become with a concept, the more efficient neural messaging between cells becomes. Once we master a skill, it takes minimal effort for the neurons to relay information to each other - the neurons essentially become wired together.

Neural Networks are not unique to humans as machines also use a similar system to learn particular tasks assigned to them. For machines Neural Networks are Deep Learning algorithms which help them learn more efficiently and improve their scores. In a machine Neural Network, neurons are arranged in three layers — Input, Hidden and Output. The Input layer directly accepts the real data values, and the Output Layer gives the final estimate of the output. These two layers are connected together by hidden layers which apply weights to the inputs and direct them through…