6 ms·
It's not penalty or step size. It's loss as in amount of information lossd (not encoded in your network) compared to one perfectly encoding ground truth. Learni
by notretarded 6y ago
It's not penalty or step size. It's loss as in amount of information lossd (not encoded in your network) compared to one perfectly encoding ground truth.
Learning rate, as in what is the maximum amount of delta you are allowed to change your inputs to minimise your information loss analogous to how quickly you can possibly learn in one experiment.
- sillysaurusx 6y agoFair. I’ll keep that in mind. On the other hand, it went way over my head, and I’m not afraid to admit it. One of the nice things about ML (and math, for that matter) is that there are multiple mathematically equivalent ways of looking at a thing.