I have a couple of questions related to the exercises in Lab2 in week 4:
In the lectures you say that if we are loading the training set using ImageDataGenerator, we should use model.fit_generator (and not model.fit) when training the CNN. Yet, in Lab 2 you use model.fit even though the ImageDataGenerator is used to load training data. Could you please clarify why model.fit is used here, or is this version-specific?
The accuracy during training at each epoch jumps up and down substantially, reaching high 90s and then dropping as low as 70s, and going back up and down again. In the lectures you mention that this can be a result of overfitting (if I remember correctly). In a real world application, in contrast to a learning exercise, would this magnitude of changes be of concern? In other words, should we be implementing some practices to avoid/fix this issue?