In reference to your point about #16: From my understanding, it makes sense to separate the loss function and the optimizer. Before you can optimize and update weights, first you must know how good/bad the current weights are. Therefore, it’s important to recognize that we need a loss function in order to train a model. Point 24 is just following up and making sure we know what a loss function is.
I was wondering if it’s ok to create blogs answering the questions in the book?
I don’t see why not!
Yes I do
Where do we set the “loss” criteria for the actual optimization method? Is it hardcoded in the “architecture” ? In codes of chapter 1, only metric is set…