Context: Machine Learning Projects are mainly just a complex interdependent pipeline. We desperately need a better abstraction for them.

Using AntiPatterns to avoid MLOps Mistakes, Nikil Muralidhar et. al.

I learned about this survey paper from The Data Exchange podcast. It’s a good introduction for people who just started deploying their machine learning project to production.

The paper focused on supervised learning, and forcasting applications. But the observation and recommendations should be general enough to be applied to other common machine learning deployments.