About us
R-Rome promotes open-source tools, collaborative learning, and accessible data science education through the R programming language.
Our group meets both in person and online to explore topics in R, data science, statistics, visualization, artificial intelligence, reproducible research, and advanced analytical tools. Whether you are just starting with R or already working professionally with data, our events are designed to support continuous learning, knowledge sharing, and community collaboration.
We believe learning should be open, practical, and lifelong. Our community encourages people from different backgrounds, disciplines, and experience levels to connect, learn together, and contribute to the broader open-source ecosystem.
Email: rome@rladies.org
Website: rladiesrome.org
More info & Contacts:
Twitter: @rladiesrome
LinkedIn: @R-Ladies Rome
GitHub: meetup-presentations_rome
YouTube: @rladiesrome
Mastodon: @rladiesrome@fosstodon.org
Our activities include workshops, talks, tutorials, study groups, and collaborative events focused on developing practical R and data science skills in an open and supportive environment. We strongly support the principles of open-source software, reproducible research, and free access to educational resources.
As a founding principle, participation in our events is free of charge. You can access presentations, R scripts, and projects through our GitHub repositories and follow our channels to stay updated on upcoming events and community initiatives.
Please make sure to read and comply with our Code of Conduct:
https://rladies.org/coc/
Please note that by participating in an R-Ladies event, you grant the organizers permission to use photographs, video recordings, and media content for communication, educational, promotional, and community-related purposes. This may include online publications, social media, newsletters, presentations, and related materials. If you do not wish to appear in photos or recordings, please inform one of the organizers.
— IN ITALIANO —
R-Rome è una comunità che promuove strumenti open source, apprendimento collaborativo e formazione accessibile nel campo della data science attraverso il linguaggio R.
Ci incontriamo sia di persona sia online per esplorare temi legati a R, statistica, data science, visualizzazione dei dati, intelligenza artificiale, ricerca riproducibile e strumenti avanzati di analisi. Che tu sia agli inizi o abbia già esperienza professionale con R e i dati, i nostri eventi sono pensati per favorire apprendimento continuo, condivisione delle conoscenze e collaborazione.
Crediamo in un apprendimento aperto, pratico e permanente. La nostra comunità incoraggia persone provenienti da percorsi, discipline e livelli di esperienza diversi a partecipare, imparare insieme e contribuire all’ecosistema open source.
La comunità organizza workshop, talk, tutorial, gruppi di studio ed eventi collaborativi per sviluppare competenze pratiche in R e nella data science in un ambiente aperto e inclusivo. Supportiamo fortemente i principi del software libero, della ricerca riproducibile e dell’accesso gratuito alle risorse educative.
Come principio fondante, la partecipazione agli eventi è gratuita. È possibile accedere a presentazioni, script R e progetti tramite i nostri repository GitHub e seguire i nostri canali per rimanere aggiornati sulle attività della comunità.
Assicurati di leggere e rispettare il nostro codice di condotta:
https://rladies.org/coc/
Si prega di notare che partecipando a un evento R-Ladies si concede agli organizzatori il diritto di utilizzare fotografie, registrazioni video e contenuti multimediali per finalità educative, comunicative, promozionali e legate alla comunità. Questo può includere pubblicazioni online, social media, newsletter, presentazioni e altri materiali correlati. Se non desideri comparire in foto o registrazioni, informa uno degli organizzatori.
Upcoming events
1
Machine Learning in Epidemiology with R — Part II: From Trees to Neural Networks
·OnlineOnlineHow do different machine-learning models learn from the same data, and how can we compare their predictions?
Join R-Ladies Rome for the second workshop in our Machine Learning in Epidemiology with R series, led by Federica Gazzelloni.
Part I introduced how models learn through loss and optimisation.
Part II, we’ll put these ideas into practice by training and comparing decision trees, random forests and a simple neural network using a heart-disease classification example.
We’ll follow a complete workflow in R: explore the data, define a prediction task, train models and evaluate their performance on observations they have not seen during training.
What we’ll cover
- Decision trees and random forests with `mlr3`.
- A simple neural network with Keras.
- Layers, activation functions, epochs and batch sizes.
- Training and validation loss.
- Model comparison using accuracy, sensitivity, specificity and ROC/AUC.
- Overfitting, cross-validation and the distinction between prediction and causation.
Who is this for?
This workshop is for people interested in applying machine learning to epidemiology and health data. Basic familiarity with R and RStudio is recommended. The session builds on Part I and begins with a short recap.What to bring
A computer with R and RStudio installed. Setup instructions and workshop materials will be shared before the session.Bring your questions and join us for a practical exploration of how different models learn—and how we assess their predictions.
22 attendees
Past events
52
