This end to end project aims to be a proof of concept of how a system that could help in the diagnosis of breast cancer could be made, finished with an API made in flask to be consumed in parallel with an application made in streamlit, in both it is possible to train and do predictions. This entire project was made with the Docker Container in mind to facilitate replication in other environments.
To run this project, run docker-compose up at terminal.
install the requirements in the files requirements-*.txt and run the files app-flask.py and/or app-streamlit.py.
- Models: stored at /models
- Scalers: stored at /scalers
- Encoders: stored at /encoders
- Data: stored at /data
- Project main code: stored at /src
This project is still in development.