Azure Machine Learning Workspace and MLOps

I discussed the Azure Machine Learning Service. The Azure Machine Learning Service is at the core of custom AI. But what really ties it together is the Azure Machine Learning workspace. The process of AI involves working with lots of data, cleaning the data, writing and running experiments, publishing models, and finally collecting real-world data and improving your models. The machine learning workspace provides you and your co-workers with a collaborative environment where you can manage every aspect of your AI projects. You can also use role-based security to define roles within your teams, you can check historical runs, versions, logs etc., and you can even tie it to your Azure DevOps repos and fully automate this process via ML Ops. In this article, I'll introduce you to all of these and more.