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 leastsquares 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