Generalized Linear ModelsCovers probability, random variables, expectation, GLMs, hypothesis testing, and Bayesian statistics with practical examples.
Probability and StatisticsIntroduces probability, statistics, distributions, inference, likelihood, and combinatorics for studying random events and network modeling.
Probability and StatisticsCovers fundamental concepts in probability and statistics, emphasizing data analysis techniques and statistical modeling.
Probabilistic Linear RegressionExplores probabilistic linear regression, covering joint and conditional probability, ridge regression, and overfitting mitigation.
Maximum Likelihood InferenceExplores maximum likelihood inference, comparing models based on likelihood ratios and demonstrating with a coin example.
