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machine-learning-apps/gke-argo
This action is a mechanism you can leverage to accomplish CI/CD of Machine Learning. This Action facilitates instantiating model training runs on the compute of your choice running on K8s, specifically on Google Kubernetes Engine.
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machine-learning-apps/actions-argo
The purpose of this action is to allow automatic testing of Argo Workflows. Argo is a mechanism you can leverage to accomplish CI/CD of Machine Learning. This Action facilitates instantiating model training runs on the compute of your choice running on K8s.
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machine-learning-apps/wandb-action
GitHub Action That Retrieves Model Runs From Weights & Biases
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azure/aml-workspace
The Azure Machine Learning Workspace action will allow you to create or connect to a Azure Machine Learning workspace so you can later run your Machine Learning experiments remotely, create production endpoints etc.
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azure/aml-compute
The Azure Machine Learning Compute action will allow you to create a new compute target or check whether the specified compute target is available so you can later run your Machine Learning experiments or deploy your models remotely.
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azure/aml-run
The Azure Machine Learning Run action will allow you to submit a run (Estimator, ML Pipeline, ScriptRunConfig or AutoMLConfig) to your Azure Machine Learning Workspace.
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azure/aml-registermodel
The Azure Machine Learning Register Model action will register your model in the Azure Machine Learning model registry for use in deployment and testing. This action is designed to only register the model, if the run has produced better metrics than the latest model that is registered under the same name.
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azure/aml-deploy
The Azure Machine Learning Deploy action will deploy your model on Azure Machine Learning and create a real-time endpoint for use in other systems.
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NikeNano/kubeflow-github-action
The purpose of this action is to allow for automated deployments of Kubeflow Pipelines on Google Cloud Platform (GCP). The action will collect the pipeline from a python file and compile it before uploading it to Kubeflow.
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See the GitHub Actions help documentation for instructions on how to add actions to your workflow.