Projects

This is a follow up to the previous post, where the mechanics of making cross-playlist predictions were covered. This post covers the second half of the project: now that we have the analysis method and the important functions worked out in practice, we need to code this functionality into a Shiny app, create a Docker container that holds and runs the app, and deploy the container on Amazon Web Services for public access.

As before, the code is available on Github. It won’t be completely replicated here due to its length.

This is the first of probably two posts detailing the construction of an RShiny app. The app in question is meant to take data from two Spotify playlists, make recommendations for tracks from one – which I’ll call the “target” playlist – based on the contents of another – the “reference” playlist. I don’t expect this to be comparable in ability to Spotify’s own system (or anything else, really), but it seems like it should be interesting.

My code is here.