This dashboard is the participation of the Machine Learning Group from the Université Libre de Bruxelles (MLG-ULB, mlg.ulb.ac.be) to the hackaton CodeVsCovid19 (www.codevscovid19.org). It provides a detailed analysis of the effect of government policies on the evolution of the COVID-19 disease.
gbonte.shinyapps.io/Shiny_App_Covid/
- Théo Verhelst (tverhels@ulb.ac.be): Team lead
- Jacopo (jdestefa@ulb.ac.be): Data preprocessing and analysis
- Gian Marco Paldino (gpaldino@ulb.ac.be): Shiny Dashboard
- Elias Fernández (eliferna@vub.be): Data preprocessing & literature research
- Mattia Bontempi: Data collection
- Gianluca Bontempi (gbonte@ulb.ac.be): Mentor
- Global time series: JHU CSSE
- Italy time series: Presidenza del Consiglio dei Ministri - Dipartimento della Protezione Civile
- Country policy dates: a Kaggle dataset
