Model Evaluation & Metrics

This tutorial explains how to evaluate machine learning models using the most important regression and classification metrics. It covers MSE, RMSE, MAE, and R² for regression, as well as Accuracy, Precision, Recall, F1-score, Confusion Matrix, and ROC-AUC for classification, with clear explanations and practical visualizations using Matplotlib and Seaborn.

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