2 years ago

Category: Kubernetes, Ubuntu

In this installment, we will start exploring building an end-to-end machine learning pipeline for data preparation, training, and inference. We will train a Convolutional Neural Network (CNN) to classify the images of dogs and cats.

In the first part of this series, we will build custom container images for the Kubeflow Notebook Server that we will use in the remainder of this tutorial.

Finally, we expose port 8888 for accessing the Jupyter Hub web interface and launch the notebook with the right set of parameters.

In the next part of this tutorial, we will configure the Kubernetes Storage Classes, Persistent Volumes required to run the Notebook Servers.