Jointprob is a probabilistic modelling and Bayesian statistics study group.
https://scicloj.github.io/docs/community/groups/jointprob/
Scicloj is an open-source group working on a stack of tools and libraries for data science using the Clojure programming language.
A few of us care a lot about the probabilistic/Bayesian paradigm and find it a promising approach in general
Moreover, we believe there are some shared core ideas in common between Clojure, the programming language, and Bayesian Statistics, the scientific method. They both seek simple, coherent, and conceptually clear solutions to problems, and they both dare to diverge from mainstream approaches to achieve that.
The Scicloj approach to building a data science stack is based on building bridges to other languages and ecosystems. This seems compatible with the spirit of the Bayesian community and its subcommunities, where different technological flavors respect and learn from each other.
Creating a polyglot study group -- one where different programming languages and styles of thinking meet to learn together -- is also a way to challenge ourselves to learn more about other ecosystems and hopefully encourage friends from those ecosystems to be curious about Clojure.
Statistical Rethinking: A Bayesian Course with Examples in R and STAN by Richard McElreath
- Around 20-25% of the group already have Clojure experience. Other folks write R, Python, or Julia
- Industry pratitioners, researchers, academics
- Statistics people
- Data engineers, data scientists, and analysts
- Biochemists, physicists, engineers
- Software developers
- One chapter every two weeks
- 3 possible time periods every two weeks
- Clojure visual-tools
- Clojure for NLP
- Intro to Clojure meetups and training
- https://jointprob.github.io/jointprob-shadow-cljs/ interactive Shadow CLJS elements for exploring Bayesian concepts
- Bayesian Analysis of soccer matches
- Bayesian Analysis of house prices
- Benefits:
- Learning together, collaboration, and community
- Cross-pollination of ideas and approaches from different programming environments
- Opportunities to introduce Clojure to with a broader audience of practitioners, building bridges
- Challenges:
- Some friction from reading an R textbook, starting to learn Clojure, while learning Bayesian statistics
- Additional side project show-and-tell and project collaboration
- Possibly starting a new text soon (subject to group discussion)
- Join the club!