3 ms·
The model knows not where it is, but it knows where it isn't. By subtracting where it is from where it isn't it obtains a difference, or gradient. Gradient is u
by H8crilA 4y ago
The model knows not where it is, but it knows where it isn't. By subtracting where it is from where it isn't it obtains a difference, or gradient. Gradient is used to generate corrective commands to drive the model from a position where it was to a position where it wasn't.