A QA kickoff slide lists linear regression, decision trees, support-vector machines, random forests, Bayesian models, and neural networks as candidate techniques for a hatchery grader. How should a tester treat those names?

Linear regression, trees, SVMs, random forests, Bayesian models, and neural nets are ML technology families a tester must recognize at awareness. This is not a library pick, not a hyperparameter search, and a random forest is not a diffusion model.