A pre-trained, sklearn model that has been trained to predict housing prices in Boston according to several features, such as average rooms in a home and data about highway access, teacher-to-pupil ratios, and so on. You can read more about the data, which was initially taken from Kaggle, on the data source site.
The project goal is to operationalize this working, machine learning microservice using kubernetes with using AWS EKS.
- Check docker lint and make sure there is no problems there.
- Build a new docker image and push it to docker.io
- Deep image inspection and vulnerability scanning.
- Create a AWS Cluster and deployment our docker image.