There is always a challenge to create a DevOps solution for machine learning projects. In this session, an overview of the machine learning process will be delivered. Using Pipeline creates a workflow with speed, portability, and reusability, and we can focus on machine learning instead of infrastructure and automation. In this session, we learned how to create a Pipeline in three main authoring environments ( Azure ML designer, Automated ML and Notobook) and use the created REST API in a project.