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This is a static snapshot from the time of the Kubeflow 1.0 release.
For up-to-date information, see the latest version.

Kubeflow Samples

Examples that demonstrate machine learning with Kubeflow

This section introduces the examples in the kubeflow/examples repository. Before using a sample, check the sample’s README file for known issues.

MNIST image classification

Last update 2023/10/19 Kubeflow v1.0.0

Train and serve an image classification model using the MNIST dataset. This tutorial takes the form of a Jupyter notebook running in your Kubeflow cluster. You can choose to deploy Kubeflow and train the model on various clouds, including Amazon Web Services (AWS), Google Cloud Platform (GCP), IBM Cloud, Microsoft Azure, and on-premises. Serve the model with TensorFlow Serving.

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Financial time series

Last update 2022/02/10 Kubeflow v0.7

Train and serve a model for financial time series analysis using TensorFlow on Google Cloud Platform (GCP). Use the Kubeflow Pipelines SDK to automate the workflow.

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Next steps

Work through one of the Kubeflow Pipelines samples.


Last modified 21.04.2020: Restructured the website repo to allow for future i18n and content translation (#1909) (d0bd0e03)