Meta learning is a branch of machine learning that deals with learning to learn. An example of this is few-shot learning where the algorithm is trying to learn from a small dataset fast by given example of many datasets similar in some way (for example that they all represent classifying different objects but that the objects present in each dataset differ).
I recently stumbled upon pytorch-meta which includes data loading functionality for the most common datasets used for meta learning. I feel that this would be a good contribution to get people to use Flux and Julia for meta learning.
Is this of interest to anyone else out there? Would be happy to work together on a package like this for Julia!