Inspiration
What inspired me was seeing other people create there own models and train them, and others such growing from such challenges.
What it does
It takes input selected from the website and sends the JSON selected from that input into Django where the model guesses what diseases those symptoms may be caused from.
How we built it
React front-end, Django back-end, I made the ml in google collab, CSS was AI generated and created the div inside of app.jsx that displays the top predictions.
Challenges we ran into
A small error in the MLB caused it to not recognize any symptoms put into it, IDE/Power shell was struggling to start up Django and react, Tailwind wouldn't install properly causing me to have to use only vanilla CSS
Accomplishments that we're proud of
I made the model on my own, created a full stack application that functions, and had a fun time creating it.
What we learned
Better understanding of React and machine learning.
What's next for ML Symptom Tracker
I plan to find a better dataset, fine tune even more, and finally deploy it
Built With
- catboost
- ccs
- django
- fpdf
- html5
- javascript
- python
- react
Log in or sign up for Devpost to join the conversation.