Ludum Dare is an online game development competition, where submissions receive a rating from 1-5 stars. This project aims to predict the rating of a project using a set of 32 diverse parameters. To achieve this, a model was developed centred around LightGBM as a multiclass classifier. In addition, images were assessed for their number of colours, and the project name and description were given a classification separately using PyTorch text classification. With tuning, this approach achieved a 94.15% accuracy, placing 1st on the class leaderboard (at the time of writing). It also demonstrated the value of practical machine learning.
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Argent: Economic Empowerment via SMS
Our final solution earned us 2nd place out of 60 teams, and $500 donation to a charity of our choice! If implemented, it would deliver $36 in Net Social Impact for every dollar invested, impact over 17,900 individuals, and generate $6 million in community impact within in 10 years! So what was our solution?
Continue reading...TOHacks 2019 Hackathon Winner: CaliOrBust
Ever wanted a Cali co-op? Well, now you can! With our new web app and voice assistant, you can practice, Cali-or-Bust, and bust again!!
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