The Kubeflow project is dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable, and scalable by leveraging best-of-breed open source projects. These include Jupyter Notebooks, TensorFlow, and Pytorch for Training; Seldon and KFServing for Serving; and Kubeflow Pipelines. These are all wrapped up neatly in an easy-to-use portal so developers and data scientists can easily collaborate and deliver production-ready AI/ML workloads.
