Introduction
When you want to implement artificial intelligence (AI) at scale, automation plays a key part. The goal is to move from experimentation to production with machine learning operations (MLOps).
There are several workloads that can be automated. To automate workloads, you'll create pipelines that group together tasks in a specific order. To automate the pipeline, you can run them at a schedule or trigger them based on an event.
You'll learn how to differentiate between the pipelines you create with Azure Machine Learning and workflows you can automate with Azure Pipelines in Azure DevOps or GitHub Actions.
Note
A pipeline is a concept that you'll find within several services in Azure. To clarify which pipeline is implied, the full product name will be included for Azure Machine Learning pipelines, Azure (DevOps) Pipelines, and GitHub Actions.
Learning objectives
In this module, you'll learn:
- How to use Azure Machine Learning pipelines.
- How to use Azure Pipelines and GitHub Actions to automate workflows.