Google search is the ultimate example (IMO) of an effective, simple, and powerful Markov chain algorithm. For anyone interested in this stuff, check out "The $

Google search is the ultimate example (IMO) of an effective, simple, and powerful Markov chain algorithm. For anyone interested in this stuff, check out "The $25 Billion Dollar Eigenvector"[0]. I did a simple page rank experiment in an IPython notebook[1], demonstrating how PageRank works based on some UBC lectures. Markov Chain Monte Carlo sampling is the basis of many Bayesian inference techniques, and Markov chains also show up extensively in classic speech recognition pipelines, under various forms of Hidden Markov Models (VB-HMM, GMM-HMM). This stuff forms the foundation of statistical machine learning! Great post - this simple example serves as a great introduction! Of course, the rabbit hole is deep... [0] http://www.rose-hulman.edu/~bryan/googleFinalVersionFixed.pdf http://www.rose-hulman.edu/~bryan/googleFinalVersionFixed.pd... [1] http://kastnerkyle.github.io/blog/2014/04/16/simple-page-rank/ http://kastnerkyle.github.io/blog/2014/04/16/simple-page-ran...