Comment by hodgehog11

No, it is relatively few words to quickly touch on several different concepts that go well beyond basic approximation theory.

I can construct a Gaussian process model (essentially fancy linear regression) that will fit _all_ of my medical image data _exactly_, but it will perform like absolute rubbish for determining tumor presence compared to if I trained a convolutional neural network on the same data and problem _and_ perfectly fit the data.

I could even train a fully connected network on the same data and problem, get any degree of fit you like, and it would still be rubbish.