Incremental fcst nb
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Description
Summary
This PR adds the starting part of the tutorial notebook: incremental_forecasting.ipynb which explains how to generate incremental forecasts using MLForecast and demonstrates the update() workflow with examples.
Changes
- Added notebook:
nbs/docs/tutorials/incremental_forecasting.ipynb
Why
This helps users adopt incremental forecast workflows and reduces the need to retrain models when new actuals arrive.
/cc @nasaul
Happy to refine further based on feedback.
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Hi @nasaul ,
Thank you for the guidance on the earlier PR. I’ve now cleaned up my fork, synced it with Nixtla’s main, and opened this fresh draft PR from a new branch as suggested. This version includes only the tutorial notebook so it should be much easier to review.
I appreciate your help and am happy to refine or adjust anything based on your feedback.
Thanks again for your time and support!
Great job Satyajit! I left you some comments. Feel free to leave a discussion if you think that my comments aren't clear enough or doesn't go well with your tutorial.
Thank you, Saul, for the valuable feedback. I have restructured the notebook, and I would be grateful if you could share your thoughts on it whenever you have time. Kind regards.
Thank you for your great job @Satyajit-Chaudhuri! The tutorial is finished. The last steps to be merged into main are the following:
- [ ] Update the branch with the latest changes from
main - [ ] Update the
docs.jsonwith the new tutorial name under thetutorialskeyword. - [ ] Update Colab link in order to direct into the main branch (it won't work until merged)
- [ ] Run the
make all_docsandmake preview_docsin order to check that the article is being rendered as intendend.
Hi @nasaul, Thanks for the kind words. I have completed the steps as mentioned in the last comment. Please let me know if anything else is required from my end. Thanks!
CodSpeed Performance Report
Merging #526 will not alter performance
Comparing Satyajit-Chaudhuri:incremental_fcst_nb (8f4ddce) with main (b6bb2e4)
Summary
✅ 12 untouched
Hey @nasaul, Thank you for the thorough review and quick merge. I really appreciate the clear feedback and the smooth, well-run review process. Glad to contribute, and looking forward to collaborating again.