azul

@all-contributors please add @jvdd for code

Hey @jvdd! Thank you! It sounds like a nice enhancement. Yes, sure! Please feel free to open a PR with your integration ❤️

Hey @NasreddineD! Thank you for using statsforecast and letting us know about the issue. Could you share a reproducible example to dig into the problem?

hey @NasreddineD! Thank you. If you include exogenous variables in your data, once you call `forecast` you have to add the exogenous variables of the future in the `X_df` argument....

@kvnkho :)

i love this. i think we should move forward with the enhancement. regarding the second drawback, i agree with the nightly wheels option. also adopting a compiled alternative will force...

@wwulfric, thanks for opening this issue. @ngupta23 i'm very excited about what we discussed. i thought that we could add different ways to calculate `season_length`, for example ``` AutoARIMA(season_length=SeasonalityACF()) ```...

hey @loama! Thank you for improving our documentation. It looks amazing. ❤️ We recently decided to manage the `styles.css` file in [this](https://github.com/Nixtla/nixtla-commons/tree/main/styles) repository. New changes are propagated through the different...

hey @msh855! Currently, statsforecast doesn't support classification problems. But it is part of our roadmap. Do you have suggestions on possible algorithms or methods you would like to have?

Fixed in #275