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Machine Learning Toolkit for Kubernetes
A guideline for building practical production-level deep learning systems to be deployed in real world applications.
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Standardized Serverless ML Inference Platform on Kubernetes
Machine Learning Pipelines for Kubeflow
Elyra extends JupyterLab with an AI centric approach.
Distributed ML Training and Fine-Tuning on Kubernetes
Automated Machine Learning on Kubernetes
Unified Interface for Constructing and Managing Workflows on different workflow engines, such as Argo Workflows, Tekton Pipelines, and Apache Airflow.
DoEKS is a tool to build, deploy and scale Data & ML Platforms on Amazon EKS
Kubeflow’s superfood for Data Scientists
Kubernetes Operator for MPI-based applications (distributed training, HPC, etc.)
Distributed Machine Learning Patterns from Manning Publications by Yuan Tang https://bit.ly/2RKv8Zo
deployKF builds machine learning platforms on Kubernetes. We combine the best of Kubeflow, Airflow†, and MLflow† into a complete platform.
Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...
👩🔬 Train and Serve TensorFlow Models at Scale with Kubernetes and Kubeflow on Azure
A curated list of awesome projects and resources related to Kubeflow (a CNCF incubating project)