True Gradient Descent

In machine learning, the effectiveness of a network is measured by an error function which measures how good a network is at its job. In general, the higher the error, the worse the network is. Conversely, the lower the error, the better the network is. When a machine is trying to learn how to do a task, it tries to make as few mistakes as possible; that is, minimize its error function. True gradient descent is the application of gradient descent to a machine learning network to minimize an error function.