Jupyter Notebooks as a Service using Kubernetes and Portworx

Jupyter Notebooks are the tool of choice for data scientists building their own Machine learning models. Kubeflow is an open-source tool that allows data scientists to get access to a Jupyter notebook on demand, without having to worry about finding or provisioning the required compute and storage resources to run their ML pipelines. In this demonstration, we look at how Portworx and Kubernetes can dynamically provision the resources needed, in order to run experiments and perform hyperparameter tuning using Kubeflow pipelines.

[@sotong1113]

Very good 👍