Über uns
From beginners to experts, professionals to amateurs, anyone with an interest in R is welcome.
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• Homepage: rusershamburg
Please adhere to R Consortium and the R Community Code of Conduct:
R Consortium and the R Community Code of Conduct
The R Consortium, like the R community as a whole, is made up of members from around the globe with a diverse set of skills, personalities, and experiences. It is through these differences that our community experiences great successes and continued growth.
Members of the R Consortium and their representatives are bound to follow this R Community Code of Conduct (which is based on the Python Community Code of Conduct). We encourage all members of the R community to likewise follow these guidelines which help steer our interactions and strive to keep R a positive, successful, and growing community.
R Community Code of Conduct
A member of the R Community is:
Open: Members of the community are open to collaboration, whether it's on projects, working groups, packages, problems, or otherwise. We're receptive to constructive comment and criticism, as the experiences and skill sets of other members contribute to the whole of our efforts. We're accepting of anyone who wishes to take part in our activities, fostering an environment where all can participate and everyone can make a difference.
Considerate: Members of the community are considerate of their peers — other R users. We're thoughtful when addressing the efforts of others, keeping in mind that oftentimes the labor was completed simply for the good of the community. We're attentive in our communications, whether in person or online, and we're tactful when approaching differing views.
Respectful: Members of the community are respectful. We're respectful of others, their positions, their skills, their commitments, and their efforts. We're respectful of the volunteer efforts that permeate the R community. We're respectful of the processes set forth in the community, and we work within them. When we disagree, we are courteous in raising our issues.
Overall, we're good to each other. We contribute to this community not because we have to, but because we want to. If we remember that, these guidelines will come naturally.
Questions/comments/reports? Please write to the Code of Conduct address: conduct@r-consortium.org. (this will email the Board Chair and R Consortium Program manager). Include any available relevant information, including links to any publicly accessible material relating to the matter.
THANK YOU to our sponsors, ...
the RConsortium, for their continuous financial support
and JobMatchMe, for regularly providing their location to host our events.
Sponsoren
Alles ansehen
virtual7Financial support for organizig meetups.
Why R?Financial support for organizing WhyR? pre-metings.
R ConsortiumFinancial support for organizing meetups.
Jumping RiversFinancial support for organizig meetups.- virtual7Financial support for organizig meetups.
- Why R?Financial support for organizing WhyR? pre-metings.
- R ConsortiumFinancial support for organizing meetups.
- Jumping RiversFinancial support for organizig meetups.
Bevorstehende Events (1)
Alles ansehen- Teaching Causality and Causal ML with Shiny AppsORBIT Ventures GmbH, Hamburg, HH
Dear R Users, we are happy to announce our next Meetup! This time it's about how R's popular framework for creating almost arbitrarily complex web applications, R-Shiny, can be leveraged to entice students to delve into data analysis/visualization and causal inference/ML within a University setting!
Besides that, as always, there will be the opportunity for a pleasant chat over a cold drink and a slice of pizza 🍕🍕🍕
Agenda
18:30 Open Door
18:50 Welcome & AOB
19:00 Teaching Causality and Causal ML with Shiny - Gangli Tan & Philipp Bach
19:45 Break
20:00 Meet the Speakers
20:30 Chill out and drinksR Shiny Apps for Teaching Causality and Causal ML
Shiny apps offer students the opportunity to interact with data and complex statistical topics without prior knowledge of coding. Students get curious about how to generate data visualizations, perform statistical analyses or develop their own apps. Our speakers Gangli and Philipp are going to share examples and experiences from teaching causal inference with shiny apps. The Digital Causality Lab (DCL) is an innovative teaching project at the University of Hamburg which focuses on the topics Causal Inference and Data Literacy. Shiny apps are an integral part of the DCL teaching materials - both as teaching devices but also as examples for student projects. A brief introduction to causality as well as an outlook to Causal Machine Learning will be part of the talk, too. Gangli and Philipp are very happy to present their project to Hamburg R Users, to get some feedback and ideas for more apps in the future!About the Speakers
Philipp Bach is a post-doctoral researcher at the Chair of Statistics with Application in Business Administration at the University of Hamburg. His research focuses on software implementations and empirical applications of causal machine learning approaches, most importantly double/debiased machine learning in R and Python. Philipp does not only enjoy teaching to students but also to data scientists from industry, mostly in the context of causal machine learning.Gangli Tan is a research assistant and PhD candidate at the University of Hamburg. She just completed a M.Sc. degree in Business Administration, majoring in Management and Marketing. She is highly interested in causal machine learning, managing AI and digital innovation and transformation in organizations. Gangli has been part of the Digital Causality Lab from the very first day and has contributed to the shiny apps and the teaching materials.
