I’m currently on week 2 (part 1 deep learning), and have started to look at applying what’s been covered so far to the Kaggle ‘Galaxy Zoo’ challenge. The problem I have is that the training data, rather than having a binary classification, has 37 probabilities, reflecting different classifications and features, as per the competition guidelines. With the dogsvscats work, the training data was divided into folders that represented the class, but that’s not possible here. Has anyone tackled this issue and if so, could you give me any hints as to how to tell keras about these training labels, and how to consequently get the predict functions to output 37 different probabilities per image.
This is all new to me, so I’m sure I’m missing something pretty basic. Thanks.