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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 p-quantile, normal approximation, joint distributions, and exponential families in probability and statistics.
Covers the fundamental concepts of probability and statistics, including interesting results, standard model, image processing, probability spaces, and statistical testing.
