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