Out of dateThis guide contains outdated information pertaining to Kubeflow 1.0. This guide needs to be updated for Kubeflow 1.1.
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 2020/07/08 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.
Financial time series
Last update 2019/12/20 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.
Work through one of the Kubeflow Pipelines samples.
Was this page helpful?
Glad to hear it! Please tell us how we can improve.
Sorry to hear that. Please tell us how we can improve.