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Python SDK for building, training, and deploying ML models
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README.md

Overview of Kubeflow Fairing

Kubeflow Fairing is a Python package that streamlines the process of building, training, and deploying machine learning (ML) models in a hybrid cloud environment. By using Kubeflow Fairing and adding a few lines of code, you can run your ML training job locally or in the cloud, directly from Python code or a Jupyter notebook. After your training job is complete, you can use Kubeflow Fairing to deploy your trained model as a prediction endpoint.

Documentation

To learn how Kubeflow Fairing streamlines the process of training and deploying ML models in the cloud, read the Kubeflow Fairing documentation.

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