About skforecast¶
History¶
skforecast was born from the need to make forecasting easy, accessible, and effective for everyone. Since its inception in 2021, our aim has been to bridge the gap between machine learning and practical time series forecasting. Thanks to our amazing community, the library continues to grow, evolve, and help people worldwide forecast better.
Governance¶
skforecast is an open-source project maintained by its core development team, with guidance and valuable contributions from the community. We strongly believe in openness, transparency, and collaboration. Everyone is encouraged to participate through issues, discussions, and pull requests on GitHub.
Core Development Team¶
Meet the core developers behind skforecast.
Main Contributors¶
Special mention to the main contributors who have significantly impacted the library development:
| Name | GitHub |
|---|---|
| Fernando Carazo Melo | @FernandoCarazoMelo |
Contributors¶
Get Involved
We value your input! Here are a few ways you can participate:
- Report bugs and suggest new features on our GitHub Issues page.
- Contribute to the project by submitting code, adding new features, or improving the documentation.
- Share your feedback on LinkedIn to help spread the word about skforecast!
Together, we can make time series forecasting accessible to everyone.
| Name | GitHub |
|---|---|
| Josh Wong | @josh-wong |
| Edgar Bahilo Rodríguez | @edgBR |
| Mwainwright | @syndct |
| Kishan Manani | @KishManani |
| Sergio Quijano | @Sergio-Quijano-Stratesys |
| Fernando da Silva | @schoulten |
| Lillian Jensen, MPH | @tyg3rr |
| Ivan Liu | @IvanLiuTW |
| Ignacio Moya | @imMoya |
| Pablo Rodríguez Pérez | @pablorodriper |
| g-rubio | @g-rubio |
Thank you for helping us make skforecast better! 🎉
Citing skforecast¶
If you use skforecast for a scientific publication, we would appreciate citations to the published software.
Zenodo
Amat Rodrigo, Joaquin, & Escobar Ortiz, Javier. (2025). skforecast (v0.15.0). Zenodo. https://doi.org/10.5281/zenodo.8382788
APA:
Amat Rodrigo, J., & Escobar Ortiz, J. (2025). skforecast (Version 0.15.0) [Computer software]. https://doi.org/10.5281/zenodo.8382788
BibTeX:
@software{skforecast,
author = {Amat Rodrigo, Joaquin and Escobar Ortiz, Javier},
title = {skforecast},
version = {0.15.0},
month = {3},
year = {2025},
license = {BSD-3-Clause},
url = {https://skforecast.org/},
doi = {10.5281/zenodo.8382788}
}
View the citation file.
License¶
Skforecast software: BSD-3-Clause License
Skforecast documentation: CC BY-NC-SA 4.0
Artwork¶
Feel free to use the official skforecast logo for presentations, blog posts, or any material mentioning or promoting skforecast:
Please do not alter, distort, or modify the original logo without permission.