Inspiration
Due to this COVID-19 pandemic, we are currently noticing a large number of mental health breakdowns especially in people working from home. So, we decided to build a project that would let people know whether their mental health is interfering with their workplace performance.
What it does
This app takes some basic inputs from the user and analyses them through a pre-trained Machine Learning model to predict whether their mental health is interfering with their workplace performance.
How we built it
- Gathered data regarding mental health from Kaggle
- Trained various Machine Learning Models and calculated their accuracy
- Choose our Random Forest Classifier model as the best one
- Made an API server with FastAPI for processing data and wrapping our model
- Built a Typeform-like form using React to gather user inputs
Challenges we ran into
- Choosing a Machine Learning model with high enough accuracy
- Building an API server for our model
- Choosing memes that can make people smile :)
- Tailoring React libraries for our needs
Accomplishments that we're proud of
We successfully overcame all the above-mentioned challenges and that's our biggest accomplishment! We also learnt how to train and deploy a Machine Learning model on a production server.
What we learned
- A lot about python backend API microservices
- Connecting a Machine Learning model with an API server for easy access from any sort of frontend framework
- Reading open source code base and trying to modify/contribute
What's next for TraumaCheck
- We'll try to suggest some solutions which will help people overcome mental health issues through the same app.
- We'll try to implement an Unsupervised dynamic Machine Learning model in future.
- Make the app responsive
Built With
- api
- axios
- fastapi
- heroku
- javascript
- jupyter-notebook
- machine-learning
- material-ui
- netlify
- numpy
- pandas
- pickle
- pydantic
- python
- react
- react-router
- redux
- scikit-learn
- scipy
- swagger
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