Optimize ML model hyperparameters using grid, random, or Bayesian search. Generate and execute validated Python code with scikit-learn or Optuna on datasets like Iris for models such as Random Forest or Gradient Boosting, retrieve performance metrics, save tuned artifacts, and generate documentation.
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