David Muhr

I just found out that it's not the fault of github runner, but there appears to be no suitable release for the [AWS Lambda docker image](https://gallery.ecr.aws/lambda/python) for `0.3.2`, but for...

So the question is how to release `manylinux1`, `manylinux2010`, `manylinux2014` and `manylinux_x_y` packages simultaneously. The [maturin docs](https://github.com/PyO3/maturin#manylinux-and-auditwheel) mention that *If you want to publish widely usable wheels for linux pypi,...

It appears that scikit-learn dropped manylinux2010 support with `1.1.0` and numpy dropped manylinux2010 support with `1.22.0`. I would propose to align with the numpy manylinux support for future releases, i.e....

Yes, it's not really documented, but apparently they support 2014+.

Wouldn't it be more intuitive/self-explanatory to add a `report` kwarg to the surrogate machine call that takes a named tuple input? It would also allow `fitted_params` if it's necessary at...

> Ah, yes, I can imagine that could be so. Does this mean we need to expedite this somewhat? Currently this is low on my priorities as I am swamped...

I'm having a difficult time converting my custom `return!` to the new MLJ API (added in https://github.com/JuliaAI/MLJBase.jl/pull/644). Previously, I could just use ```julia function return_with_scores!(network_mach, model, verbosity, scores_train, X) fitresult,...

Thank you for your detailed thoughts on how we could go forward. I need some more time to think about it. I'm a bit afraid of feature creep in MLJ,...

I would prefer to keep the API simple with a `report` that can flexibly accommodate predictions, transformations or whatever the algorithm could produce. Strangely enough, `predict(model, fitresult, Xtrain)` would NOT...

> 1. So, does this interface rule out some clustering models we have yet to encounter? > Are there further requirements should we impose? I think this is also a...