About us
We seek to connect experienced and aspiring data professionals in Maine by offering an engaging forum to share ideas and learn from each other. Topics include everything from data engineering, analytics, statistics, machine learning, and AI.
The Greater Portland R User Group was initially founded in 2018 as a way to bring the R Users of Portland Maine together. With the hopes of becoming a state-wide user group, we have renamed to the MaineR Users Group.
The goal of this group is to explore and discuss R and how it is being used in data science, data analysis, visualization, data mining, predictive analytics, and beyond!
People of all levels are welcome to attend, from those just getting started with R and predictive modelling to experts using R every day. While the focus is on the R programming language, presentations / talks from other languages/ fields are more than welcome!
Have Questions?
- email us at: maine.r.user.group@gmail.com
Visit us at:
Upcoming events
2
MaineR Online Talk July 2026
·OnlineOnlineJoin us for a short, but sweet 30-40 minute talk given by Emil Hvitfeldt, software engineer at Posit PBC!
The talk is titled:
"Moving the modeling into the database with {orbital}"
MaineR locals will meet in the evening at 5:30 to de-brief on the talk and enjoy a few beers together.
- Link to the registration/call is posted here on the event and sent out the the mailing list.
Moving the modeling into the database with {orbital}
Orbital, a new tool that converts scikit-learn (Python) or tidymodels (R) workflows into native SQL for in-database prediction. It’s perfect for regulated or resource-constrained environments where deploying Python/R runtimes is a pain, and it can even be faster (think Snowflake wins) than running via Python services.
What you’ll learn—quick hits:
- How Orbital turns trained pipelines into portable SQL for real-time inference
- When to prefer in-database scoring (security, scaling, governance)
- Hopefully: A live, end-to-end demo from model to SQL (R + Python perspectives)
- Performance notes (e.g., Snowflake) and gotchas to watch for
- Practical tips for deployment and team workflows, plus Q&AEmil Hvitfeldt is a software engineer at Posit and part of the tidymodels team’s effort to improve R’s modeling capabilities. He maintains several packages within the realms of modeling, text analysis, and color palettes. Trying to make slidecrafting a well respecting verb. He co-authored the book Supervised Machine Learning for Text Analysis in R with Julia Silge. Working on book Feature Engineering A-Z.
Contact Dave with any questions!
7 attendees
Past events
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