Neural Networks: 1-Layer Networks

[@anantchopra1663]

A wonderful explanation for any beginner! Thank you, Prof. Brunton and Prof. Kutz, for making quality content freely available to all of us.

[@gordonsowner]

From the book and from here... on the formula around the 5:00 mark. I don't get the argmin over A_j, with your regularizer being lambda * g(A_j). That seems like you are picking an A_j from over all of the layers as a solution. It seems like you need to find a method that determines *all* of the A_j layer weights. I just am not understanding this formulation. I'd get if you'd take the argmin over all of the layer weights A_j (j=1..M) of the nested function, but again, I'm not understanding the argmin over different A_j, with the regularizer term. A bit more explanation would be very very helpful I think.

[@NormanLim]

In section 4, they gave a formula similar to that -- formula 4.3a -- as an "overall mathematical framework when considering regression to nonlinear models"

[@alexanderskusnov5119]

Doesn't AI see cat's wiskers?