Data Science: Model Evaluation and Validation Professional

Model evaluation, using techniques like Cross-Validation, measure a model’s effectiveness. Model validation, through processes such as Hyperparameter Tuning, ensures that the model performs well on unseen data.

These steps are important in building trustworthy and effective machine learning systems.

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