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Bias-Variance Trade-OffExplores underfitting, overfitting, and the bias-variance trade-off in machine learning models.
Model Selection: AIC and BICExplores model selection using AIC and BIC criteria, addressing different questions and the importance of sparsity in selecting the best model.
Model EvaluationExplores underfitting, overfitting, hyperparameters, bias-variance trade-off, and model evaluation in machine learning.
Generalization TheoryExplores generalization theory in machine learning, addressing challenges in higher-dimensional spaces and the bias-variance tradeoff.
Model Building: Linear RegressionExplores model building in linear regression, covering techniques like stepwise regression and ridge regression to address multicollinearity.