For my 3-week Insight Data Science Fellowship project in 2018, I used data from the Steam game store to build an app called Playful to make computer game recommendations for Steam users using collaborative filtering with implicit feedback. The app isn't live anymore because I stopped paying for the AWS instance, but all the code and details you would need to recreate it are here.
First, I obtained Steam data and performed some initial data exploration using
- scrapy
- API calls
- PostgreSQL
Next I generated, optimized, and validated a collaborative filtering model with implicit feedback using
- sparse matrices
- matrix factorization
- recall@k
Finally I built a web app to turn that model into recommendations for anyone who owns games on Steam using
- item-to-item recommendations
- pandas
- flask
- Amazon web services
More details are in this notebook.