ML Ops was very confusing to me at first. People were telling me it was useful, but would never tell me what it was. In this video I explain what ML Operations is (ML Ops), where it came from, and why learning it could be useful for your career.
ML Ops came from Development Operations (devops). Dev ops are essentially anything that facilitates the collaboration between software teams or it operations teams. The goal is to make software repeatable, testable, and scalable.
So how is ML Ops different?
-Focus on exclusively ML projects
-Different data needs than most software projects
-Different types of testing and experimentation
-Different tools used to monitor ML models
Best place to learn ML ops is on the job. Still projects, conversations, communities, etc. are great!
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