How to: Machine Learning Ops
- [Submitting Argo Workflows (Cloud Agnostic)](https://github.com/machine-learning-apps/actions-argo)
- [Submitting Argo Workflows to GKE](https://github.com/machine-learning-apps/gke-argo)
- [Query Experiment Tracking Results From Weights & Biases](https://github.com/machine-learning-apps/wandb-action)
- [Run Parameterized Jupyter Notebooks](https://github.com/yaananth/run-notebook)
- [Compile, Deploy and Run Kubeflow Pipeline](https://github.com/NikeNano/kubeflow-github-action)
- [Automatically Dockerize A Data-Science Repo As A Jupyter Server](https://github.com/jupyterhub/repo2docker-action)
- [Azure Machine Learning With GitHub Actions](https://github.com/machine-learning-apps/ml-template-azure)