With microk8s setup, I was ready to try out first time workflow based upon the venerable MNIST image set.
Creating a Notebook Server
First off, I needed to launch a Jupyter Notebook on the Kubernetes cluster. Following this tutorial,
After a minute or so, the notebook shows as ready:
Clicking Connect takes opens the new Notebook:
MNIST Sample Project
To verify the Notebook server is working, I tried a created Python3 workbook and pasted some sample code:
Ignoring the deprecation errors, this sample downloaded a MNIST data set and ran a gradient descent training and output the accuracy value. In my case: 0.9002.
More in this series…
- microk8s on ubuntu - Single instance cluster
- microk8s upgraded - Upgrading to k8s 1.19
- kubeflow setup - Enabling ML workflows
- kubeflow pipelines - Deploying pipelines on Kubeflow