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.