This lecture concerns Probabilistic Graphical Models and, in particular, Bayesian networks. The outline is the following: first, motivation and generalities about Probabilistic Graphical models, then the specific model called Bayesian networks. In more detail, we will talk about the definition of such networks and two main operations: inference (given the BN) and construction of a BN (given data).
Deep Learning 05 - Probabilistic Graphical Models - part 1
Cristina De Castro
2019
Abstract
This lecture concerns Probabilistic Graphical Models and, in particular, Bayesian networks. The outline is the following: first, motivation and generalities about Probabilistic Graphical models, then the specific model called Bayesian networks. In more detail, we will talk about the definition of such networks and two main operations: inference (given the BN) and construction of a BN (given data).File in questo prodotto:
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