Ah yes - that sounds like the stochastic gradient descent I've been hearing about. That makes a lot of sense for very expensive models. Thanks for the response nshm - I've recently taken an interest in ML (coming in…
Do you mean to say that it is possible to design your parameters over all inputs without gradient descent? I'm somewhat confused, as I think that that would not be possible in the general case (e.g. nonlinear problems…
Ah yes - that sounds like the stochastic gradient descent I've been hearing about. That makes a lot of sense for very expensive models. Thanks for the response nshm - I've recently taken an interest in ML (coming in…
Do you mean to say that it is possible to design your parameters over all inputs without gradient descent? I'm somewhat confused, as I think that that would not be possible in the general case (e.g. nonlinear problems…