The Why R? pre-meeting will happen in Gdansk :)
The first part of the meeting:
Tomasz Wąs- Network analysis
In the modern world, we are surrounded by a great variety of networks. Financial systems, Internet and citation networks are just a few examples. In many of them, we are interested in finding their key element. Is it possible to obtain, knowing only the network’s structure?
Here, the centrality measures come in. They directly indicate the importance of a node in a given graph. However, due to their number and variety, the choice between them is not an easy one. The choice that has a substantial impact on obtained results. In my talk I will point out how, using axiomatization, we can help with this choice and make the results more interpretable.
The second part of the meeting:
Mikołaj Bogucki - Shiny workshop
Always wanted to learn how to share the results of your analysis in a stunning fashion? Shiny is a web framework for R that allows to quickly create complex, interactive data dashboards. Shiny is easy to learn and is gaining popularity worldwide.
This workshop will cover basics of Shiny app creation process. We’ll go through:
creating shiny app project,
creating static and dynamic interface elements,
writing server app logic,
basics of reactive programming,
tying it up together.
Basic, general knowledge of R is highly recommended.
Tomek Wąs is interested in both the financial mathematics, the field of his postgraduate studies, and the network analysis, the subject of his current PhD studies at the University of Warsaw. For combining them in his master’s thesis, he was awarded the first prize in Data Science Masters contest. Now, he publishes on the top AI conferences. On a personal note, cinephile, and offbeat beer enthusiast.
Mikołaj Bogucki is an experienced Data Scientist and also an experienced teacher. Currently holding a Senior Data Science position at Pearson, the leading worldwide learning company. He's also the co-founder of iDash, a startup providing high quality Data Science training. He’s passionate not only about R, Shiny and Data Science in general but also about how people learn and interpret surrounding reality.