using IBCF algorithm to predict user ratings based on rated items and output a list of recommended items
- data folder contains original beeradvocate data set from data.world
- RData contains data objects to enable fast deployment of R shiny app
- www contains bootstrap.css
- prep.R prepares data, creates recommender objects
- server.R has app logic
- ui.R has front-end appearance
- testing.R has evaluation of recommender system
To run locally, download project and run server.R/ui.R or go to https://wasencroll.shinyapps.io/beer-recommender/ and see it in action online!
Visit https://www.alexandercroll.com/site/portfolio/beer-recommender to read a more detailed summary or download the full .pdf paper!