Tutorial: Introduction to Kubeflow Pipelines
In this session, you will learn how to install and use Kubeflow Pipelines to create a full machine learning application on Kubernetes.Starting with an empty environment, you will create a Kubernetes c …
| Talk Title | Tutorial: Introduction to Kubeflow Pipelines |
| Speakers | Michelle Casbon (Senior Engineer, Google), Dan Anghel (Strategic Cloud Engineer, Google), Michal Zylinski (Cloud Customer Engineer, Google), Dan Sanche (Developer Programs Engineer, Google) |
| Conference | KubeCon + CloudNativeCon Europe |
| Conf Tag | |
| Location | Barcelona, Spain |
| Date | May 19-23, 2019 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | |
In this session, you will learn how to install and use Kubeflow Pipelines to create a full machine learning application on Kubernetes.Starting with an empty environment, you will create a Kubernetes cluster and install Kubeflow from scratch. Then you will build and run a full pipeline that first trains a model using TensorFlow, then serves the model, and finally deploys a web front-end for interacting with the resulting predictions. You will then move into a notebook to build and run your pipeline using the Python SDK.You will become familiar with Google Cloud Platform tools such as Cloud Shell and Kubernetes Engine.Prerequisite: fundamental knowledge of Kubernetes.Setup: must bring own laptop. Qwiklab/GCP credits will be provided.Note: this session showcases Kubeflow features newly released since the Seattle workshop.
