so I just watched first 3 lessons and I wanted to make sure that I understand everything before I move on. (I will make sure to do the assignment and apply my new skills on some kaggle datasets for sure).
So there are some things that I still don’t understand like “precompute=True” but I am pretty that this is explained somewhere on the forums.
So I would like to ask more about the things that just aren’t clear to me.
when we use the Data augmentation does it increase the size of our dataset by a factor of 6 or does it just use a different version of the same image in every epoch?
another thing that isn’t clear to me is the image sizes. I understand that if you have 500x400 image you can just crop 224x224 chunk from the middle, but in the cats vs dogs dataset there are some images that have a dimension that is smalled than 224. So does the Convnet fill the remaining area with white pixels or how is this problem handled?
in function ‘most_by_correct’ there is this line
mult = -1 if (y==1)==is_correct else 1
I am actually not sure what the condition does there and if it affects the mult variable or not.
Also if there is someone who is also relatively new or someone who is feeling like coaching a newbie you can add me on discord snek#0551