# Learning Probabilistic Graphical Models in R

David Bellot (지은이) | Packt Publishing | 2016-04-29

250쪽 | 235*191mm | 언어 : English | 국가 : 영국 | 435g | ISBN : 9781784392055

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해당 도서는 2016년에 출간된 1판 이며, 한글번역판은 출간되지 않았습니다.[(알라딘 참조)](http://www.aladin.co.kr/search/wsearchresult.aspx?SearchTarget=All&SearchWord=Learning+Probabilistic+Graphical+Models+in+R&x=0&y=0)

목차는 다음과 같습니다.

1: Probabilistic Reasoning
2: Exact Inference
3: Learning Parameters
4: Bayesian Modeling – Basic Models
5: Approximate Inference
6: Bayesian Modeling – Linear Models
7: Probabilistic Mixture Models
Appendix A: Appendix
Appendix B: Index

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[Probabilistic Graphical Models] Introduction and Overview:[무난무난님 블로그(한글)](http://fabj.tistory.com/12)

CS 228: Probabilistic Graphical Models Lecture Notes:[텐서플로우 블로그 (Tensor ≈ Blog)(한글)](https://tensorflow.blog/2017/04/25/cs-228-probabilistic-graphical-models-lecture-notes/)

Probabilistic Graphical Models:[coursera(영문)](https://www.coursera.org/specializations/probabilistic-graphical-models)

Probabilistic Graphical Models:[Eric Xing(영문)](http://www.cs.cmu.edu/~epxing/Class/10708-14/lecture.html)



## 출처

* https://www.clien.net/service/board/jirum/10887317?po=0&od=T31&sk=&sv=&category=&groupCd=