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   * Week 8: {{:ml7-generative.pdf|Generative Models and Parameter Estimation}} : generative models in general; maximum likelihood estimation; Bayesian Learning; Gaussian, logistic regression, Multinomial, Markov chains, GMM.    * Week 8: {{:ml7-generative.pdf|Generative Models and Parameter Estimation}} : generative models in general; maximum likelihood estimation; Bayesian Learning; Gaussian, logistic regression, Multinomial, Markov chains, GMM. 
  
-  * Week 9: Graphical models: Bayesian Networks vs Markov random fields;  Conditional independence; Inference in graphical models; belief propagation; variational inference+  * Week 9: {{:ml8-graphicalmodel.pdf|Graphical models}}: Bayesian Networks vs Markov random fields;  Conditional independence; Inference in graphical models; belief propagation; variational inference
lecture_notes.1572882892.txt.gz · Last modified: 2019/11/04 15:54 by hj