4304b20afa
auto-ml-forecasting-bike-share.ipynb crashes in cell using shutil.copy2() under some versions of Python in the local environment. Change to shutil.copy() so it works in most Python environments.
Examples to get started with Azure Machine Learning service
Learn how to use Azure Machine Learning services for experimentation and model management.
As a pre-requisite, run the configuration Notebook notebook first to set up your Azure ML Workspace. Then, run the notebooks in following recommended order.
- train-within-notebook: Train a model hile tracking run history, and learn how to deploy the model as web service to Azure Container Instance.
- train-on-local: Learn how to submit a run to local computer and use Azure ML managed run configuration.
- train-on-amlcompute: Use a 1-n node Azure ML managed compute cluster for remote runs on Azure CPU or GPU infrastructure.
- train-on-remote-vm: Use Data Science Virtual Machine as a target for remote runs.
- logging-api: Learn about the details of logging metrics to run history.
- production-deploy-to-aks Deploy a model to production at scale on Azure Kubernetes Service.
- enable-app-insights-in-production-service Learn how to use App Insights with production web service.
Find quickstarts, end-to-end tutorials, and how-tos on the official documentation site for Azure Machine Learning service.