Introduces key concepts in probability and statistics, such as events, Venn diagrams, and conditional probability.
Covers the fundamental concepts of probability and statistics, including interesting results, standard model, image processing, probability spaces, and statistical testing.
Explores probabilistic linear regression, covering joint and conditional probability, ridge regression, and overfitting mitigation.
Introduces key concepts in probability and statistics, covering random experiments, events, intersections, unions, and more.
Introduces fundamental probability concepts, including events, complements, conditional probability, and random variables.
Covers the basics of probability theory, including definitions, calculations, and important concepts for statistical inference and machine learning.
Introduces key statistical concepts like probability, random variables, and correlation, with examples and explanations.
Covers p-quantile, normal approximation, joint distributions, and exponential families in probability and statistics.
