Bernoulli distribution

Related lectures (30)

Page 2 of 3

Discusses parameter estimation, including checks, quality, distribution, and statistical properties of estimates.

Explores exponential families, Bernoulli distributions, parameter estimation, and maximum entropy distributions in statistical modeling.

Explores Bernoulli trials, independent trials, and the binomial distribution.

Introduces the fundamentals of supervised learning, including loss functions and probability distributions.

Covers the definition of variance, examples, theorems, and applications in probability theory.

Explores Bernoulli and K properties in smooth dynamics, including equivalence, examples, and implications.

Covers properties and transformations of discrete random variables, focusing on PMF and expectation.

Explores independent and identically distributed random variables, convergence, and distribution properties.

Covers the basics of probability distributions, including mean, variance, and properties of random variables.

Covers exponential family distributions, natural parameters, sufficient statistics, and logistic regression.