lorenzoh

At some point we'll have to think about iterable datasets and at that point some rearchitecting DataSets.jl could be useful. It should also not be too hard to add iterable...

Some are being added in #163

Hey! The list above is uptodate. The easiest thing to get started with should be adding recipes for the csv datasets and registering some `TableDatasetRecipe`s.

Might need a new recipe type that wraps `TableRecipe`, but can't say without looking at the folder structure

I think in this case it may be possible to create a new recipe that wraps `TableRecipe` (which loads the table) and then reads in the labels and converts label...

That’s a good idea!

I think the mid-level abstractions are sufficiently generic 👍 I'm not familiar with the SOTA in time series, but here's a list of things that I think would need to...

I'm gathering a lot of common computer vision functionality in FastAI.jl's [`Vision` submodule](https://github.com/FluxML/FastAI.jl/tree/master/src/Vision). FastAI.jl is the batteries-included deep learning package that brings together many of the packages that you end...

> What about higher having level standard preprocessing function, e.g. for ImageNet and CIFAR10 Once we do this for multiple datasets, this would become a bit unwieldy and maybe too...

Support in Pollen.jl for documenting multiple versions kinda works but is not great rn, i.e. no GitHub Action when a new version is tagged, no version picker in the frontend....