Inspiration - Educational Dropout is one of the worst things that can happen to an individual, stunting their growth and opportunity. This app is built to combat just that.
What it does - It is trained on a Kaggle dataset that predicts whether a student is a dropout or not and I made a Random Forest Classifier. The app allows for the user to upload a csv file and the model predicts the probability of each person dropping out and shows each individual statistics. Based on that, the user can make hypothetical changes to a person's tuition fees of courses, for example, and see how probability of dropping out is affected.
How we built it - I used HTML/CSS, Python, and Flask to build this app.
Challenges we ran into - I struggled with logical and syntactical errors throughout the day.
Accomplishments that we're proud of - I came up with an idea quickly and implemented an MVP that I hope to build on later on.
What we learned - I learned the importance of persisting a model, as it makes the website much less computationally intensive.
What's next for EduTracker - Ran out of time for this (On slides).
Slides: https://docs.google.com/presentation/d/1LGOuFrjqrSD7T3HoftwUm4a6tYyiP90kGkB4p-8R26I/edit#slide=id.g322f0e8252b_0_0
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