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Using causal techniques, we aim to develop **intelligent strategies for data analysis** that surpass the correlation based approach of classical statistics, in order to **distill robust causal information** from our data.
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We meet every 3 weeks for a virtual session of 1 hour, according to our [meeting schedule](https://gitlab.com/daniel.gruenbaum/causal-inference-wiki/-/wikis/Meeting-schedule). The meetings feature talks from group members, discussion about current challenges in our daily work and the sharing of useful causality resources. If you are interested in joining the conversation, please contact causal-inference@posteo.de. The project has just started and we would love to bring together even more people who are curious about causal data science! Previous knowledge of causal inference is not necessary, but it might be helpful to be familiar with some basics of statistics, data science and machine learning.
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We meet every 3 weeks for a virtual session of 1 hour, according to our [meeting schedule](https://gitlab.com/daniel.gruenbaum/causal-inference-wiki/-/wikis/Meeting-schedule). The meetings feature talks from group members, discussion about current challenges in our daily work and the sharing of useful causality resources. **If you are interested in joining the conversation, please contact causal-inference@posteo.de.** The project has just started and we would love to bring together even more people who are curious about causal data science! Previous knowledge of causal inference is not necessary, but it might be helpful to be familiar with some basics of statistics, data science and machine learning.
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This wiki serves as a place to share causality related material such as papers, books or video tutorials. You can navigate through its pages by using the navigation bar to the right.
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If there is a topic that you would like to introduce to the group, feel free to **create a page** about it! |
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