[D] How to build ML systems: from MLOps to Machine Learning Pipelines

MLOps is often thrown out as the solution to "productionizing ML". However, existing courses, blog posts, and books start from "learn Docker, kubernetes, Terraform, etc". The MLOps vendors confuse matters - Google's MLOps mental map has 26 boxes to build (worst lego instructions ever!), while Databricks has even more (to show off their production-ready guns).


I developed a free serverless machine learning course, where you built a serverless ML system from 3 Python programs (ML pipelines that create features, models, …

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