- A machine learning project deployment scenario with multiple applications / docker containers
- The main code for training the model can be found in another repo
- The project involves a streamlit application for the frontend and a FastAPI application for the backend / ML service
- Run the following command to build the container for backend
cd backend/
docker build -t ml_water_potability_backend -f backend.dockerfile .
- Run the following command to build the container for frontend
cd frontend/
docker build -t ml_water_potability_frontend -f frontend.dockerfile .
- Run the following command (in the same directory with the docker-compose.yaml file) to deploy and run both the containers
docker-compose up