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1 | 1 | +++
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2 | 2 | title = "Codelabs, Workshops, and Tutorials"
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3 |
| -description = "Recommended end-to-end tutorials, workshops, walk-throughs, and codelabs" |
| 3 | +description = "Recommended end-to-end tutorials, workshops, walk throughs, and codelabs" |
4 | 4 | weight = 20
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5 | 5 | +++
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6 | 6 |
|
7 |
| -{{% blocks/content-item title="OpenShift Kubeflow Workshop" |
8 |
| - url="https://github.com/AICoE/openshift_kubeflow_workshop" %}} |
9 |
| -Run Kubeflow on Red Hat [OpenShift](https://www.openshift.com/). |
10 |
| -{{% /blocks/content-item %}} |
| 7 | +## Agile Stacks Kubeflow Pipelines tutorials |
11 | 8 |
|
12 |
| -{{% blocks/content-item title="Agile Stacks Kubeflow Pipelines Tutorial" |
13 |
| - url="https://www.agilestacks.com/tutorials/ml-pipelines" %}} |
14 | 9 | Run Kubeflow Pipelines tutorials on AWS, GCP, or on-prem hardware using [Agile Stacks](https://www.agilestacks.com/).
|
15 | 10 | Pipeline templates provide step-by-step examples for working with object storage filesystem, Kaniko, Keras, and Seldon.
|
16 |
| -{{% /blocks/content-item %}} |
17 |
| - |
18 |
| -{{% blocks/content-item title="Katacoda scenarios" |
19 |
| - url="https://www.katacoda.com/kubeflow" %}} |
20 |
| -Follow the tutorials to deploy Kubeflow and run a machine learning model. |
21 |
| -{{% /blocks/content-item %}} |
22 |
| - |
23 |
| -{{% blocks/content-item title="Introduction to Kubeflow Codelab" |
24 |
| - url="https://codelabs.developers.google.com/codelabs/kubeflow-introduction/index.html" %}} |
25 |
| -Run MNIST with Kubeflow on Google Kubernetes Engine. |
26 |
| -{{% /blocks/content-item %}} |
27 |
| - |
28 |
| -{{% blocks/content-item title="Introduction to Kubeflow Qwiklab" |
29 |
| - url="https://www.qwiklabs.com/catalog_lab/933" %}} |
30 |
| -Run MNIST with resources provided by Qwiklabs. |
31 |
| -{{% /blocks/content-item %}} |
32 |
| - |
33 |
| -{{% blocks/content-item title="Kubeflow End to End Codelab" |
34 |
| - url="https://codelabs.developers.google.com/codelabs/cloud-kubeflow-e2e-gis/index.html" %}} |
35 |
| -Run GitHub Issue Summarization with Kubeflow on Google Kubernetes Engine. |
36 |
| -{{% /blocks/content-item %}} |
37 |
| - |
38 |
| -{{% blocks/content-item title="Kubeflow End to End Qwiklab" |
39 |
| - url="https://www.qwiklabs.com/catalog_lab/1046" %}} |
40 |
| -Run GitHub Issue Summarization with resources provided by Qwiklabs. |
41 |
| -{{% /blocks/content-item %}} |
| 11 | + |
| 12 | +* [ML Pipeline Templates: End-to-end Tutorial](https://www.agilestacks.com/tutorials/ml-pipelines). |
| 13 | + |
| 14 | +## Google codelabs |
| 15 | + |
| 16 | +Google Developers Codelabs provide a guided, tutorial, hands-on coding experience. |
| 17 | + |
| 18 | +* [Introduction to Kubeflow on GKE](https://codelabs.developers.google.com/codelabs/kubeflow-introduction/index.html): Run MNIST with Kubeflow on Google Kubernetes Engine (GKE). |
| 19 | + |
| 20 | +* [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. |
| 21 | + |
| 22 | +* [Kubeflow Pipelines - GitHub Issue |
| 23 | + Summarization](https://codelabs.developers.google.com/codelabs/cloud-kubeflow-pipelines-gis/index.html): Run GitHub Issue Summarization with Kubeflow Pipelines on GKE. |
| 24 | + |
| 25 | +## Katacoda scenarios |
| 26 | + |
| 27 | +Follow the [Katacoda tutorials](https://www.katacoda.com/kubeflow) to deploy Kubeflow and run a machine learning model. |
| 28 | + |
| 29 | +* [Deploying GitHub Issue Summarization with |
| 30 | + Kubeflow](https://www.katacoda.com/kubeflow/scenarios/deploying-github-issue-summarization). |
| 31 | +* [Deploying |
| 32 | + Kubeflow](https://www.katacoda.com/kubeflow/scenarios/deploying-kubeflow). |
| 33 | +* [Deploying Kubeflow with |
| 34 | + ksonnet](https://www.katacoda.com/kubeflow/scenarios/deploying-kubeflow-with-ksonnet). |
| 35 | +* [Deploying Pytorch with |
| 36 | + Kubeflow](https://www.katacoda.com/kubeflow/scenarios/deploy-pytorch-with-kubeflow). |
| 37 | + |
| 38 | +## OpenShift Kubeflow workshops |
| 39 | + |
| 40 | +Run Kubeflow on [Red Hat OpenShift](https://www.openshift.com/). |
| 41 | + |
| 42 | +* [Kubeflow on OpenShift Workshop](https://github.com/AICoE/openshift_kubeflow_workshop). |
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