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chore(README): Update Kubeflow Pipelines on Tekton blog #10482

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merged 1 commit into from Feb 15, 2024
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chore(README): Update Kubeflow Pipelines on Tekton blog #10482

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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -56,7 +56,7 @@ The meeting is happening every other Wed 10-11AM (PST)
* [Part 1: How to create and deploy a Kubeflow Machine Learning Pipeline](https://towardsdatascience.com/how-to-create-and-deploy-a-kubeflow-machine-learning-pipeline-part-1-efea7a4b650f)
* [Part 2: How to deploy Jupyter notebooks as components of a Kubeflow ML pipeline](https://towardsdatascience.com/how-to-deploy-jupyter-notebooks-as-components-of-a-kubeflow-ml-pipeline-part-2-b1df77f4e5b3)
* [Part 3: How to carry out CI/CD in Machine Learning (“MLOps”) using Kubeflow ML pipelines](https://medium.com/google-cloud/how-to-carry-out-ci-cd-in-machine-learning-mlops-using-kubeflow-ml-pipelines-part-3-bdaf68082112)
* [Kubeflow Pipelines meets Tekton](https://developer.ibm.com/blogs/kubeflow-pipelines-with-tekton-and-watson/) (By Animesh Singh)
* [Tekton optimizations for Kubeflow Pipelines 2.0](https://developer.ibm.com/blogs/awb-tekton-optimizations-for-kubeflow-pipelines-2-0) (By Tommy Li)
## Acknowledgments

Kubeflow pipelines uses [Argo Workflows](https://github.com/argoproj/argo-workflows) by default under the hood to orchestrate Kubernetes resources. The Argo community has been very supportive and we are very grateful. Additionally there is Tekton backend available as well. To access it, please refer to [Kubeflow Pipelines with Tekton repository](https://github.com/kubeflow/kfp-tekton).