Thanks for doing this for all of us Jeremy & Rachel!
I have two questions re Lesson 1:
Regarding the Cyclical Learning Rate paper: Is there a way we can use this method to determine the optimum learning rate even when our loss function isn’t SGD? For example, what if our loss function is a combination of two different losses or what if it’s something like Entropy loss?
Where to put the sample images for the homework assignment: In the video, Jeremy asked us to put a few images from 2 classes of our choice and train the network on those classes. In the data subfolder, we already have the dog and cat subfolders. Do we remove that and put in our new image class folders? If we don’t, then the network is trying to classify 4 different categories right?