I’m reading this for fun—tutorials and book recommendations on the Bayesian methods toolboox with a cognitive science/machine learning slant. Comes from the Computational Cognitive Science Lab at Berkeley. I recommend the general 2008 tutorial.
Useful stuff included in tutorial:
Parameter estimation
Model selection
Why Occam’s Razor emerges naturally from the Conservation of Expected Evidence
Bayesian Methods Reading List
I’m reading this for fun—tutorials and book recommendations on the Bayesian methods toolboox with a cognitive science/machine learning slant. Comes from the Computational Cognitive Science Lab at Berkeley. I recommend the general 2008 tutorial.
Useful stuff included in tutorial:
Parameter estimation
Model selection
Why Occam’s Razor emerges naturally from the Conservation of Expected Evidence
Graphical models
Hierarchical Bayesian models