Nathaniel Yellin, a 16-year-old student, has concluded a new study that reveals the significant gender bias in the sports media coverage of female athletes and, in particular, college basketball players. Yellin has pursued his passions for sports, data science and inspiring change through the creation of an organization and interactive R Shiny application SIDELINED.
16-Year-Old Data Scientist Creates R Shiny App to Champion Gender Equality in Sports Media Coverage of NCAA Women’s Basketball
Video Highlights: Maching Learning in R – Three Reasons to Use tidymodels
The following video presentation comes from my favorite Meetup group “LA R users group”, a 2,200+ member group that puts on some amazing virtual presentations. This talk centers around that fact that modeling and machine learning in R involve a bewildering array of heterogeneous packages, and establishing good statistical practice is challenging in any language. The tidymodels collection of packages offers a consistent, flexible framework for your modeling and machine learning work to address these problems.