In this post, you will learn about how metamorphic testing could be used for performing quality control checks/testing on Machine Learning models. It is primarily meant for data science specialists to plan the test cases to test the Machine Learning (ML) model implementation from a QA perspective.
Testing Machine Learning models from a quality assurance perspective is different from testing Machine Learning models for accuracy/performance.
Back in November last year, Forrester posted an article with a stark warning: "AI hard-fact — treat it like a plug-and-play panacea and fail." The hype surrounding Artificial Intelligence (AI) has only grown since then.
Today, a cursory Google search of the term "AI" results in 2.4 billion entries. That’s a lot of AI chatter! While a Google search may be a blunt instrument for measuring the true impact of AI, it does illustrate just how "big" it has grown. If your inbox is anything like mine, I’m sure you’re only too aware that AI-everything is being used to solve AI-anything. That is exactly why Forrester’s prediction was so apt.
