MilanoR Staff is happy to announce the 9th MilanoR Meeting!
The meeting will take place on November 20th, from 7pm to about 9:30 pm, in Mikamai (close to the Pasteur metro station) [save the date, more info soon]
This time we want to focus on a specific topic: data visualization with R.
We are curious to see if there are interesting contributions about this topic within the community. Then: have you build a gorgeous and smart visualization with R, or developed a package that handle some data viz stuff in a new way? Have you created a Shiny HTML widget or a dashboard that has something new to say? Do you feel you have something to input, o you can recommend someone?
Send your contribution at admin[at]milanor[dot]net: you may present it at the 9th MilanoR meeting!
If you want to contribute but you cannot attend the meeting, you can send your contribution as a short video (3/4 minutes long) atadmin[at]milanor[dot]net. Videos may be published in the blog and played at the meeting before or after presentations.
MilanoR community grows with every R user contribution!
(If you want to get inspired, here you can find all the presentations from our past meetings)
What is a MilanoR Meeting?
A MilanoR meeting is an occasion to bring together the R users in the Milano area to share knowledge and experiences. The meeting is open to beginners as well as expert R users. Usually we run two MilanoR meetings each year, one in Autumn and one in Spring. We are now running the 9th MilanoR meeting edition.
A MilanoR meeting consists of 2-3 R talks and a free buffet offered by our sponsors, to give plenty of room for discussions and exchange of ideas: the event is free for everyone, but a seat reservation is needed. Registration will open soon, stay tuned!
The post 9th MilanoR meeting on November 20th: call for presentations! appeared first on MilanoR.
R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more…
Source:: R News