Planet Classification Challenge

[jeremy (Jeremy Howard)]

@harry

What is the point of changing the size of the images, freezing the layer, training, unfreezing and fitting again. Is that intended to counter overfitting?

What is happening to the layers of the network when we call learn.set_data(). Is it stripping off later layers and adding new ones or is just adding layers onto the end?

We only used data.resize() when we set sz=64. Since it’s so much faster, why didn’t we use that function again when we had the other sizes? Is that only included in the notebook to show a faster way resizing could be done, even though it’s not really necessary on this data set?

Yes, changing size is designed to avoid overfitting.

set_data doesn’t change the model at all. It just gives it new data to train with.

Once the input size is reasonably big, the preprocessing no longer is the bottleneck, so resizing to 128x128 or larger doesn’t really help.