This project repo consists of the following:
Along with resources available in this repository, a version of this demo was presented at DevConf.CZ March 2021, “Beyond Inference: Bringing ML into Production.” The video is available here and slides avaiable here.
To learn how to use this demo, look at the “Getting Started” guide here.
The notebook showcases how to set up a connection between a machine learning model deployed with Seldon Core and a Jupyter notebook. It also investigates how models make decisions with an explainability algorithm.
In order to deploy the model in your own Kubernetes environment, you can use the Custom Resource Definition (CRD) provided. This step is not necessary for those using the Operate First environment.