Now that you understand the basics of running workloads as experiments that leverage data assets and compute resources, it's time to learn how to orchestrate these workloads as pipelines of connected steps. Pipelines are key to implementing an effective Machine Learning Operationalization (ML Ops) solution in Azure, so you'll explore how to define and run them in this session.

1. Machine Learning
Workflows

2. Eng Teong Cheah
Microsoft MVP

3. What is a Pipelines?

4. Pipelines as Executable Processes

5. Pipeline Steps?

6. Machine Learning
Workflow
https://ceteongvanness.wordpress.com/2022/10/01/
create-a-pipeline/

7. References
Microsoft Docs