Model Registry provides a single pane of glass for ML model developers to index and manage models, versions, and ML artifacts metadata. It fills a gap between model experimentation and production activities. It provides a central interface for all stakeholders in the MLOps lifecycle to collaborate on ML models.
Updated 2025-07-16 16:37:04 +08:00
Kubernetes operator for managing the lifecycle of Apache Spark applications on Kubernetes.
kubernetes
kubernetes-operator
spark
apache-spark
kubernetes-crd
google-cloud-dataproc
kubernetes-controller
Updated 2025-07-15 05:14:43 +08:00
Kubernetes Operator for MPI-based applications (distributed training, HPC, etc.)
Updated 2025-07-12 14:24:39 +08:00
Repository used to main group ACLs used by Kubeflow developers
Updated 2025-07-12 11:38:03 +08:00
Kubeflow Central Dashboard is the web interface for Kubeflow
Updated 2025-07-12 10:17:52 +08:00
Kubeflow Pipelines on Tekton
Updated 2025-07-12 09:36:44 +08:00
Machine Learning Pipelines for Kubeflow
Updated 2025-07-12 00:31:40 +08:00
Automated Machine Learning on Kubernetes
kubernetes
machine-learning
kubeflow
ai
tensorflow
huggingface
llm
mlops
jax
pytorch
hyperparameter-tuning
neural-architecture-search
automl
scikit-learn
Updated 2025-06-26 22:13:16 +08:00
Distributed ML Training and Fine-Tuning on Kubernetes
kubernetes
huggingface
ai
llm
gpu
jax
kubeflow
distributed
xgboost
machine-learning
mlops
python
pytorch
tensorflow
fine-tuning
Updated 2025-06-20 16:05:11 +08:00
A CLI for Kubeflow.
Updated 2025-06-06 20:24:03 +08:00
Machine Learning Toolkit for Kubernetes
kubernetes
machine-learning
kubeflow
tensorflow
ml
notebook
google-kubernetes-engine
jupyter
minikube
Updated 2025-06-04 20:36:14 +08:00