# Probabilistic Graphical Models

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Another Coursera class!

Probabilistic Graphical Models

## Notes

- Model is a declarative representation, that can be turned in different algorithms. Separate model from algorithm.
- probability = lets us deal with uncertainty; established learning methods
- graphical = complex systems through (graphs); joint distributions large, need to exploit structure
- intuitive and compact data structure
- directed and undirected, such as temporal and plate models
- conditioning (conditional probability) / reduction
- marginalization -> throw away
- factor