MCMC, Renormalization, and the Ising Model

The Ising model is a simplified description of ferromagnetism where spin-up and spin-down states sit on a d-dimensional lattice with an interaction defined between spins on neighboring sites. In one and two dimensions this model is analytically soluble, but because of that it makes a perfect playground to learn about Markov Chain Monte Carlo methods; a powerful tool with diverse applications in Bayesian statistics, statistical mechanics, and quantum field theory.

Understanding Similarity With Markov Chains

Facebook is a graph. Twitter is a graph. The internet is a graph. Almost any other kind of data you can think of probably has some sort of graph structure. So if you're a data scientist, it's pretty important to know how to deal with graphs. It's a common question to ask how one can find things that are similar in a graph, but finding a good answer may not be as simple as you think