Machine learning engineering involves iterative experimentation with models and tuning hyperparameters to improve performance. Skills in using tools like Grid Search, Random Search, Bayesian Optimization, or specialized libraries such as Optuna or Hyperopt are necessary for systematic model optimization.
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