Explores probabilistic linear regression, covering joint and conditional probability, ridge regression, and overfitting mitigation.
Explores continuous random variables, density functions, joint variables, independence, and conditional densities.
Covers the fundamental concepts of probability and statistics, including interesting results, standard model, image processing, probability spaces, and statistical testing.
Delves into probability, statistics, paradoxes, and random variables, showcasing their real-world applications and properties.
Covers p-quantile, normal approximation, joint distributions, and exponential families in probability and statistics.
Introduces key concepts in probability and statistics, such as events, Venn diagrams, and conditional probability.
Introduces key statistical concepts like probability, random variables, and correlation, with examples and explanations.
