The machine learning toolkit for Kubernetes.
The Kubeflow project is dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable and scalable. Our goal is not to recreate other services, but to provide a straightforward way to deploy best-of-breed open-source systems for ML to diverse infrastructures. Anywhere you are running Kubernetes, you should be able to run Kubeflow.
Kubeflow 2020 Projects
Build a UI to Deploy Managed Tensorboard Instances with Support for PVCsMany Data Scientists have their data saved in a PersistentVolumeClaim accessed by their Notebooks. So it would be helpful and greatly improve...
Create a sample for notebook to Kubeflow deployment using TensorFlow 2.0 KerasKubernetes is already an industry-standard in managing cloud resources. Kubeflow is on its path to become an industry standard in managing machine...