Find out why backpropagation and gradient descent are key to prediction in machine learning, then get started with training a simple neural network using gradient descent and Java code.

Its derivative (slope) instantly becomes a finite (and constant) value, again portrayed in the lower graph. Next, the function continues to increase, but at a lesser rate (its slope still has a finite ...

Yes, this would be the slope of the function. That gives me the average rate of change of position during the time interval t 1 to t 2 . In physics, we would also call this the average x velocity.