Hello everyone! Time sure flies fast and it’s almost the end of October! For those who participated in Hacktoberfest, congratulations! I hope it went well and amazing.
As for me, though I initially wanted to participate as well, I found Facebook’s 2020 Developer Circles Community Challenge to be interesting, so I decided to sign up for that instead.
Hence, I built a project with a friend throughout the month of October to submit it for the hackathon. The hackathon finally ended and so in this article, I’d like to share with you what I’ve built, challenges I’ve faced and how I overcome them.
Gameo is a game recommendation engine that helps anyone to discover and play games. Using a matrix factorization-based model built with PyTorch, Gameo recommends users games via collaborative filtering.
To use Gameo, simply create an account and add games you’ve played to your Library.
Then rate them from 1 to 10 so the model learns which types of games is more suited to your personal preferences.
And that’s the gist of how Gameo works! It was a pretty fun and challenging project for me.
Challenges I’ve Faced
This is the first time I’m using PyTorch to implement a matrix factorization model and that alone makes this project quite a challenge to build.
Matrix factorization is a class of collaborative filtering algorithm.
Learn more about collaborative filtering in this article.
1. Machine Learning and PyTorch
It is an unfamiliar territory for me. I used to try working with Tensorflow for a bit but it was difficult to pick up for a beginner.