The session is designed for virtual attendees seeking a practical and conceptual understanding of statistical modeling. Participants will explore key techniques for model selection, including AIC, BIC, and cross-validation, alongside regularization methods like LASSO, Ridge, and Elastic Net. Through intuitive explanations and hands-on demonstrations in R, the session emphasizes balancing model accuracy, complexity, and interpretability. Whether you're refining predictive models or ensuring robust inference, this guided tour will enhance your ability to build reliable models and make data-driven decisions using the powerful tools within R.

Kolkata R UseR Group

Samrit Pramanik

Luong Vuong

Simisani Ndaba

goajao

Sumanta Chatterjee

belluadsm

Christiana Agbo 

Courage Eli Yevugah

majumdertannistha

gulshan.crj26

osmanibrahim

Wanessa Alves Lima

Indrajeet Kundu

Naimul Islam

theophilusdorsaahzumah

Jaiganesh C

Leo Langat Maina

no.1comforter

Jane Monkah

divakar7674

Navigating Model Selection & Regularization: A Journey through R

Online event

Targeted Maximum Likelihood Estimation (TMLE) is a powerful, flexible framework for drawing causal conclusions from observational data. Unlike traditional statistical methods, TMLE is designed to explicitly target the causal parameter of interest, combining machine learning with rigorous statistical theory to reduce bias and improve efficiency. In this session, we’ll build TMLE from the ground up and explore how it enables us to emulate randomized controlled trials using real-world data, even in the presence of confounding and missingness.

MaineR Users Group

Donald Szlosek

Dave Baker

Manish Yadav

Zahra JahediBashiz

John Zastrow

Dan Feldman

Jayden Butts

ptriplett2009

Federica Gazzelloni

Benedict Nguimbis

Nicolò Foppa Pedretti

Florencia Grattarola

Enrico Pegoraro

Mohamad 

cmanolakis2

nihadkannur

Valerio Ficcadenti

markltaper

Nick G

Introduction to Targeted Maximum Likelihood Estimation from scratch

There will be refreshments and networking from 18h00.
Agenda
\~\~\~\~\~\~\~\~\~\~\~\~
\* Meeting start at 16h30
\* 16h30 - 16h55 Welcome and News - Handre Williams
\* 17h00 - 17h55 Unveiling Causal Inference in R: From Fundamentals to Industry Applications and the AI Future with Edzai Conilias Zvobwo

* Demystifying causal inference, explaining its importance in answering “why” and “what if” questions beyond traditional correlation-based analytics. Through a hands-on R demo, we’ll explore a real-world industry application—evaluating a marketing campaign’s impact on sales using propensity score matching and causal forests. The session will conclude with a look at the future of causal inference in the AI era, highlighting its growing role in tech, healthcare, and policy, followed by a Q&A. Attendees will leave with practical R tools, resources, and inspiration to apply causal inference in their own work.

\* Meeting finish at 18h00

Details
\~\~\~\~\~\~\~\~\~\~\~\~
When: 10th June 2025 @ 16h30 to 18h00 (GMT+2)
Where: Microsoft Campus in Bryanston, South Africa
Location: https://goo.gl/maps/4ffcC3N6T7S2
Keen to speak at a user group event? Submit your session abstracts at https://sessionize.com/johannesburg-r-user-group/

Social
\~\~\~\~\~\~\~\~\~\~\~\~
Please follow us on our social media links below to stay up to date on future events:
\* Website: https://www.rusergroup.co.za
\* Meetup: https://www.meetup.com/joburg-r-users-group
\* Twitter: https://twitter.com/JHBRUserGroup
\* GitHub: https://github.com/rusergroupcoza
\* WhatsApp: https://bit.ly/3CeDifS

Johannesburg R User Group (R Programming Language)

Luis de Sousa

Handre Williams

Bonginkosi Linda Nkosi

Godfrey Ngwato

Edzai Zvobwo

tembisactv

Cliff S

Blessing

tusmun93

Austin

Mwenya Kalenga

Tendai Dupwa

Enofirstsolution (PTY) LTD

zuzethedeveloper

Fanie

Sabelo Sibanda

Rudi Laing

David Clark

Dan Tshisungu

Unveiling Causal Inference in R

Microsoft Bryanston Office

There will be refreshments and networking from 18h00.
Agenda
\~\~\~\~\~\~\~\~\~\~\~\~
\* Meeting start at 16h30
\* 16h30 - 16h55 Welcome and News - Handre Williams
\* 17h00 - 17h55 Unveiling Causal Inference in R: From Fundamentals to Industry Applications and the AI Future with Edzai Conilias Zvobwo
Demystifying causal inference, explaining its importance in answering “why” and “what if” questions beyond traditional correlation-based analytics. Through a hands-on R demo, we’ll explore a real-world industry application—evaluating a marketing campaign’s impact on sales using propensity score matching and causal forests. The session will conclude with a look at the future of causal inference in the AI era, highlighting its growing role in tech, healthcare, and policy, followed by a Q&A. Attendees will leave with practical R tools, resources, and inspiration to apply causal inference in their own work.
\* Meeting finish at 18h00
Details
\~\~\~\~\~\~\~\~\~\~\~\~
When: 10th June 2025 @ 16h30 to 18h00 (GMT+2)
Where: Room 6.49 PD Hahn Building, North Lane, University of Cape Town, South Africa
Location: https://maps.app.goo.gl/b4Mc32AshaBir5MH7
This meetup will be in collaboration with RUG Joburg. Cape Town will join this meeting online.
\* Note - no laptops are required for this event

Cape Town R User Group

Jared Norman

Johann

RUG CPT Meetup and Talk

Join the online Office Hour to

\- discuss how to get started contributing to R
\- get help/feedback on contributions you are working on
\- look at open bugs/work on translations together

R Contributors

Ella Kaye

Heather Turner

R Contributor Office Hour (EMEA/APAC)

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