Next up in the Codecademy CS Certification course is a recommendation engine. I wrote one that does a simple video game recommendation and returns 5 titles from one of 5 genres and allows the player to see a blurb about any of the titles from that list.
The previous project focused on something with practical application to my current line of work, a financial calculator for loans and savings dividends. This one was geared more towards a hobby that I find myself engaging with less and less as I get deep into learning about computer science: video games.
I sourced ratings for rankings from MetaCritic, but decided to use the player review scores rather than the reviewer scores for simplicity sake, as MetaCritic reports reviewer scores on a 100 scale and user scores on a 10 scale.
The app runs with graphs and vertices. I used dicts to store the keys and values for the games and ratings, as well as for blurbs. I wrote a helper to auto load the data into the graph for the main script.
This exercise also inspired me to start a personal portfolio project that will also use graphs, but allow me to work more with a TreeNode system as I haven't done much with that.
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