Evaluation in NLPDelves into NLP evaluation, covering gold standards, precision, recall, and statistical significance.
Probabilistic Linear RegressionExplores probabilistic linear regression, covering joint and conditional probability, ridge regression, and overfitting mitigation.
Cross-validation & RegularizationExplores polynomial curve fitting, kernel functions, and regularization techniques, emphasizing the importance of model complexity and overfitting.
Metrics for ClassificationCovers sampling, cross-validation, quantifying performance, optimal model determination, overfitting detection, and classification sensitivity.
