MachineLearningNotebooks

Why we included this project

Learning the Azure Machine Learning service is easier when you can follow along in working notebooks, and Microsoft's collection gives you that. The examples walk through the Python SDK end to end: you provision compute, register datasets, train models, let AutoML handle the tuning, and publish trained artifacts as services. Quickstarts get you running on a compute instance quickly, with deeper how-tos on pipelines, deployment, and automated ML after that. One honest caveat before you invest time: this repo targets the v1 SDK, which Microsoft has deprecated and no longer monitors, pointing users to the v2 samples in azureml-examples instead. So treat these notebooks as reference material for learning how the platform works, not a template for fresh production work. Teams already on Azure ML will still find the notebook structure a useful model for their own internal examples.