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<@U03SA41952R> and <@U03UX9KR75W>: this might be a good moment to build the MLFLOW tutorial.

this is assigned to me :sweat_smile:. I can try to get it done this week

<@U03SA41952R> do you have an update on this? also, is it possible to use kubeflow for nixtla libs?

Hey Arun, sorry I’ve been busy I wasn’t able to get to it. I’ll do it for sure tomorrow! I think you should be able to use Kubeflow. You mean in a pipeline?

thanks <@U03SA41952R>, right, in the pipeline

I think you would just call Nixtla in the pipeline right?

I agree, kubeflow should be fine. I look forward to the mlflow doc.

The PR is out <https://github.com/Nixtla/statsforecast/pull/676/|here> but you can also check the version <https://mlflavors.readthedocs.io/en/latest/examples.html#statsforecast|here> for the MLFlow integration

The PR is the same, it just cleans it up a bit and simplifies

Thank you so much <@U03SA41952R> <@U035DR8HD6D>

<@U03SA41952R> We use the cloudpickle for the MLForecast, do you have a similar doc for MLForecast (like you have for StatsForecast)?

I don’t think there is…I could make one this Friday. Asking <@U03UX9KR75W> to confirm we don’t have a doc for MLFlow + MLForecast?

We don't. I've also thought of adding save and load methods that remove attributes that aren't required for inference, so it's probably best to wait for those, WDYT?

<@U03SA41952R> <@U03UX9KR75W> morning folks! would be great to have a write up for this even for the existing features, appreciate the help here!

Will talk to Jose about it after some items I’m working on