Neural networks were based on the functioning of neurons in the brain. Dendrites in the brain receive input signals from the neighboring neurons. Each dendrite has a weight associated with it and the signal coming in from a specific dendrite gets multiplied by its corresponding weight. These incoming signals are then summed up in the cell body. As this summed-up value reaches a particular threshold, the summed-up signal is then sent across through the neuron's axon and is further propagated forward. The weights associated with a dendrite dictate the importance of the signal coming in through a particular dendrite. These values get changed dynamically. ANNs build upon the same context. Let's look at the structure of a basic ANN in the next section.
Neurons
An ANN is an interconnected network of neurons. Each neuron, as shown in the diagram at the end of this section, receives n input signals that are nothing but a set of features,...
