Support Vector Machine
Maximum-margin classification, hinge loss, kernels, and primal-dual formulations.
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Multinomial Logistic Regression
Softmax probabilities, likelihood derivations, and estimation for multiclass outcomes.
Binary Logistic Regression
Modeling binary outcome probabilities through likelihood estimation and Bayesian inference.
Bayesian Linear Regression
Posterior inference and prediction in linear regression with Gaussian and Laplace priors.
Linear Regression
Least squares, likelihood estimation, and ridge, lasso, and elastic-net regularization.