Probabilistic Linear RegressionExplores probabilistic linear regression, covering joint and conditional probability, ridge regression, and overfitting mitigation.
Generalized Linear ModelsCovers probability, random variables, expectation, GLMs, hypothesis testing, and Bayesian statistics with practical examples.
Supervised Learning EssentialsIntroduces the basics of supervised learning, focusing on logistic regression, linear classification, and likelihood maximization.
