Introduces key concepts in probability and statistics, such as events, Venn diagrams, and conditional probability.
Explores probabilistic linear regression, covering joint and conditional probability, ridge regression, and overfitting mitigation.
Covers the fundamental concepts of probability and statistics, including interesting results, standard model, image processing, probability spaces, and statistical testing.
Introduces key concepts in probability and statistics, covering random experiments, events, intersections, unions, and more.
Explores conditional probability, the law of total probability, Bayes' theorem, and prediction decomposition.
Covers p-quantile, normal approximation, joint distributions, and exponential families in probability and statistics.
