GitHub Actions relevant to machine learning and data science, that you can use to automate tasks. These are free to use and are open source.
Great Expectations - CI/CD For Data Pipelines
Validate the integrity of your data and the health of your data pipelines.
Dockerize GitHub repositories automatically as a Jupyter Server
Automatically Dockerize GitHub repos and serve their contents with the appropriate dependencies with Jupyter or R-Markdown. Can optionally be used in a complimentary way with mybinder.org
Submit Argo Workflows To GKE
Instantiate machine learning pipelines using Argo on Google Kubernetes Engine.
Submit Argo Workflows on K8s (Cloud agnostic)
Instantiate machine learning pipelines using Argo on any Kubernetes cluster. This action is cloud agnostic.
Fetch metrics from Weights & Biases
Retrieve model metrics and metadata from Weights & Biases. You can use this for automated testing and reporting in pull requests.
Compile, deploy and run Kubeflow pipelines
Launch Kubeflow pipelines on Google Cloud.
Create Azure ML Workspace
Creates an Azure Machine Learning workspace.
Manage Azure Compute Resources
Create, destroy and modify Azure compute resources.
Azure ML Run Jobs
Run a training job, experiment or pipeline on Azure.
Azure ML Register Models
Register a model on Azure Machine Learning.
Azure ML Deploy Models
Deploy a model to AKS or ACI for inference.