You can adapt the configuration to choose the platforms and services that you want to use for each stage of the ML workflow: data preparation, model training, prediction serving, and service management.
You can choose to deploy your Kubernetes workloads locally, on-premises, or to a cloud environment.
Easy, repeatable, portable deployments on a diverse infrastructure.
Kubeflow is an open source artificial intelligence / machine learning (AI/ML) tool that helps improve deployment, portability and management of AI/ML models. Kubeflow allows users to quickly create, train and tune neural networks within Kubernetes for dynamic resource provisioning.