Neural networks learn by adjusting numeric values called weights and thresholds. A weight specifies how strong of a connection exists between two neurons. A threshold is a value, stored on each neuron that either adds or subtracts from the incoming weights from other neurons. Training is
the process by which these weights and thresholds are adjusted to cause the neural network to produce useful results.