We’ll walk through the concepts and features of MLflow support in Azure Machine Learning. We’ll be showing a few examples on how to manage your machine learning assets using MLflow in variety of workflows including GitHub Actions.
- [01:00] What is Mlflow?
- [02:16] Why MLflow is useful
- [03:35] Intro to using AzureML and MLflow together
- [05:20] Demo – How to start tracking with MLflow in AzureML
- [08:00] Demo – Using MLflow Projects with AzureML
- [10:33] Why use MLflow and AzureML together
- [16:23] Walk through CI/CD example with MLflow, AzureML and GitHub Actions
- MLflow Tracking for ML experiments – Azure Machine Learning | Microsoft Docs
- MachineLearningNotebooks/how-to-use-azureml/ml-frameworks/using-mlflow at master Azure/MachineLearningNotebooks (github.com)
- MachineLearningNotebooks/how-to-use-azureml/track-and-monitor-experiments/using-mlflow at master · Azure/MachineLearningNotebooks (github.com)