A Machine Learning Microservice with a model that has been trained to predict housing prices in Boston according to several features.
The model is served through an endpoint in a Flask app.
- Create a virtualenv and activate it
- Run
make install
to install the necessary dependencies
- Standalone:
python app.py
- Run in Docker:
./run_docker.sh
- Run in Kubernetes:
./run_kubernetes.sh
- Setup and Configure Docker locally
- Setup and Configure Kubernetes locally
- Create Flask app in Container
- Run via kubectl