+++
title = "Codelabs, Workshops, and Tutorials"
description = "Recommended end-to-end tutorials, workshops, walk throughs, and codelabs"
weight = 20
+++

## Agile Stacks Kubeflow Pipelines tutorials

Run Kubeflow Pipelines tutorials on AWS, GCP, or on-prem hardware using [Agile Stacks](https://www.agilestacks.com/).
Pipeline templates provide step-by-step examples for working with object storage filesystem, Kaniko, Keras, and Seldon.

* [ML Pipeline Templates: End-to-end Tutorial](https://www.agilestacks.com/tutorials/ml-pipelines).

## Google codelabs

Google Developers Codelabs provide a guided, tutorial, hands-on coding experience.

* [Introduction to Kubeflow on GKE](https://codelabs.developers.google.com/codelabs/kubeflow-introduction/index.html): Run MNIST with Kubeflow on Google Kubernetes Engine (GKE).

* [Kubeflow End to End - GitHub Issue Summarization](https://codelabs.developers.google.com/codelabs/cloud-kubeflow-e2e-gis/): Run GitHub Issue Summarization with Kubeflow on GKE.

* [Kubeflow Pipelines - GitHub Issue
  Summarization](https://codelabs.developers.google.com/codelabs/cloud-kubeflow-pipelines-gis/index.html): Run GitHub Issue Summarization with Kubeflow Pipelines on GKE.

## Katacoda scenarios

Follow the [Katacoda tutorials](https://www.katacoda.com/kubeflow) to deploy Kubeflow and run a machine learning model.

* [Deploying GitHub Issue Summarization with
  Kubeflow](https://www.katacoda.com/kubeflow/scenarios/deploying-github-issue-summarization).
* [Deploying
  Kubeflow](https://www.katacoda.com/kubeflow/scenarios/deploying-kubeflow).
* [Deploying Kubeflow with
  ksonnet](https://www.katacoda.com/kubeflow/scenarios/deploying-kubeflow-with-ksonnet).
* [Deploying Pytorch with
  Kubeflow](https://www.katacoda.com/kubeflow/scenarios/deploy-pytorch-with-kubeflow).

## OpenShift Kubeflow workshops

Run Kubeflow on [Red Hat OpenShift](https://www.openshift.com/).

* [Kubeflow on OpenShift Workshop](https://github.com/AICoE/openshift_kubeflow_workshop).
