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.
Cross-validation & RegularizationExplores polynomial curve fitting, kernel functions, and regularization techniques, emphasizing the importance of model complexity and overfitting.
Bias-Variance Trade-OffExplores underfitting, overfitting, and the bias-variance trade-off in machine learning models.
