Azure ML Pipeline Example

This repository contains example code for using Azure Machine Learning Pipelines:

• How to define them

• How to publish and update them

• How to trigger them via their REST endpoints

• How to schedule them

How to use the example code

1. Change .azureml/config.json so it points to your Azure ML workspace.

2. Create and activate the conda environment on your machine: From within the repo directory, first run

   $ conda env create

   then run

   $ conda activate azure_ml_pipeline_example

3. Have a Service Principal (= technical user) created and put its details in config.py. For more info on authentication in Azure ML, see this site.

4. Now that the environment is set up, you can run

   $ python azure_ml_pipeline_example.py

Further Reading

• Introductory Article about Azure ML pipelines

• Example Notebooks