Data Science: Model Evaluation and Validation
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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Keywords: MachineLearningModelEvaluation, ModelPerformanceMetrics, GeneralizationError, OverfittingvsUnderfitting, Overfitting vs Underfitting.
