26. Overview of artificial neural networks

Artificial neural networks are computational systems that can be trained to perform tasks by learning from examples, generally without having to be programmed with any task-specific rules. Its functionality is supposed to mimic a biological neural system, wherein neurons interact by sending signals to each other. In the computer, these signals are generated by mathematical functions in nodes organized in connected layers. All layers can contain an arbitrary number of nodes, and each connection is represented by a weight variable.