Kubeflow
The machine learning toolkit for Kubernetes.
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.
2020 Program
Successful Projects
Contributor
Kostas Andriopoulos
Mentor
elikatsis, Kimonas Sotirchos
Organization
Kubeflow
Build a UI to Deploy Managed Tensorboard Instances with Support for PVCs
Many Data Scientists have their data saved in a PersistentVolumeClaim accessed by their Notebooks. So it would be helpful and greatly improve...
Contributor
Yash Jakhotiya
Mentor
Ce Gao, ChanYiLin, Yuan Tang
Organization
Kubeflow
Create a sample for notebook to Kubeflow deployment using TensorFlow 2.0 Keras
Kubernetes is already an industry-standard in managing cloud resources. Kubeflow is on its path to become an industry standard in managing machine...