Game Library

• 

  game favorites page

• 

  homepage

Inspiration

We have avid video game players in our team and noticed the lack of common software to track games owned and that you have played, that includes games from different platforms. Most gaming software currently only tracks games from a specific platform, so we wanted to make something that would track games across many platforms. This app gives recommendations for new games for users to try based on their current games as well!

What it does

Game Library is a web application where users can track the video games they own, and get recommendations for new games to try based on what they own.

How we built it

• MongoDB
• React.js
• Sklearn
• Figma

Challenges we ran into

Not having experience with the tools used (React, Sklearn, and MongoDB), and having issues with scheduling and time constraints. There were git conflict issues as well.

Accomplishments that we're proud of

Creating Figma mockups, implementing front end pages with React, creating the ml recommender with the sklearn library using feature extraction and tfidf vectorizer, and extracting data from an external games API: https://www.igdb.com/api

What we learned

Machine learning with sklearn, React, solving git conflicts.

What's next for Game Library

Refining the project and adding more use cases.

Team Leader

oreoz#1432

Built With

• css3
• html5
• javascript
• mongodb
• python
• react
• sklearn