Neural Networks: What are they and why do they matter?

A node is patterned after a neuron in a human brain. Similar in behavior to neurons, nodes are activated when there is sufficient stimuli or input. This activation spreads throughout the network, creating a response to the stimuli (output). The connections between these artificial neurons act as simple synapses, enabling signals to be transmitted from one to another. Signals across layers as they travel from the first input to the last output layer – and get processed along the way.

When posed with a request or problem to solve, the neurons run mathematical calculations to figure out if there’s enough information to pass on the information to the next neuron. Put more simply, they read all the data and figure out where the strongest relationships exist. In the simplest type of network, data inputs received are added up, and if the sum is more than a certain threshold value, the neuron “fires” and activates the neurons it’s connected to.