WARNING: This article may be obsoleteThis post was published in 2021-10-23. Obviously, expired content is less useful to users if it has already pasted its expiration date.
This article is categorized as "Garbage" . It should NEVER be appeared in your search engine's results.主要内容：
Gamma distribution
继续昨天的bayesian inference
Expectation Propagation和K-L散度
指数分布族的期望与方差
Gamma distribution
🔗 [39 - The gamma distribution - an introduction - YouTube] https://www.youtube.com/watch?v=J0Yzmb_PY3Y
🔗 [怎么来理解伽玛（gamma）分布？ - 知乎] https://www.zhihu.com/question/34866983
继续昨天的bayesian inference
昨天接触的都是均匀分布情况下的prior，接下来考虑这两种情况的bayesian inference：normal distribution和normal-gamma distribution.
从这篇pdf开始：🔗 [bayesGauss.dvi] https://www.cs.ubc.ca/~murphyk/Papers/bayesGauss.pdf
normal distribution的推导 🔗 [Normal prior Normal likelihood Normal posterior distribution - YouTube] https://www.youtube.com/watch?v=c-d05z0_5mw
normal-gamma的入门介绍 🔗 [The Normal-Gamma Conjugate Family - Bayesian Statistics - YouTube] https://www.youtube.com/watch?v=MNP9yr1uhvQ
normal-gamma的推导：🔗 [Bayes_Unit5] http://seor.vse.gmu.edu/~klaskey/SYST664/Bayes_Unit5.pdf ，第25页开始
🔗 [高斯分布的贝叶斯推断 · prml] https://mqshen.gitbooks.io/prml/content/Chapter2/gaussian/bayesian_inference_gaussian.html
🔗 [Chapter 4 Inference and Decision-Making with Multiple Parameters | An Introduction to Bayesian Thinking] https://statswithr.github.io/book/inference-and-decision-making-with-multiple-parameters.html
Expectation Propagation和K-L散度
🔗 [slidescharlesuniversityep2013.pdf] https://jmhldotorg.files.wordpress.com/2013/11/slidescharlesuniversityep2013.pdf
🔗 [tan.pdf] https://www.cs.ubc.ca/~murphyk/Teaching/CS532c_Fall04/Projects/tan.pdf
🔗 [4.3.2-LogisticReg] https://cedar.buffalo.edu/~srihari/CSE574/Chap4/4.3.2-LogisticReg.pdf
🔗 [paper.dvi] http://mlg.eng.cam.ac.uk/pub/pdf/KimGha08.pdf
🔗 [05.kapoor-ahn-picard.pdf] https://affect.media.mit.edu/pdfs/05.kapoor-ahn-picard.pdf
指数分布族的期望与方差
with one parameter: 🔗 [Exponential Family: Mean and Variance - YouTube] https://www.youtube.com/watch?v=wDpotV98qK0
[Exponential Family of Distributions] https://brunomaga.github.io/Exponential-Family-Distributions