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As suggested on Reddit, it would be nice to have more tutorials.
A simple idea is to base them on our existing examples. The tutorial could explain how each implemented method works and contrast it with other meta-learning methods. In doing so, it could also cover functionalities that learn2learn provides.
The text was updated successfully, but these errors were encountered:
I think even making the existing tutorials more digestible would really help. For example, adding comments in the code, putting them into Jupyter NBs and adding some level of prose in the notebooks (.md cells) would make it an easier onboard for users.
Are you guys considering adding an example for cifar100 on maml, it would be great as a lot of custom datasets has structures that could be directly applied with cifarfs.py.
As suggested on Reddit, it would be nice to have more tutorials.
A simple idea is to base them on our existing examples. The tutorial could explain how each implemented method works and contrast it with other meta-learning methods. In doing so, it could also cover functionalities that
learn2learn
provides.The text was updated successfully, but these errors were encountered: