Material covered

  • A quick sketch of Bayesian learning
  • First example: coin tossing
  • Review of Bernoulli, binomial distributions, gamma and beta functions
  • Review of multinomial distribution and Dirichlet distribution
  • Laplace smoothing with uniform prior over coin parameter
  • Second example: linear least-squares fitting from a Bayesian perspective
  • How the Bayesian approach leads to Ridge penalty
  • Solving least square and Ridge regression, the "hat matrix"

Last modified: Saturday, 25 August 2007, 10:16 AM