Who Wants to Know the Inner Workings of LDA?

In our recent series of blog posts on Topic Models, we've tried to explore this powerful new resource in the BigML Dashboard, in the API, using WhizzML, and we have also suggested some uses for it. But we've left a nuts and bolts description of how Latent Dirichlet Allocation (LDA) works until the end. Within this post, the last of a series of six posts, we'll try here to give you exactly that: A high-level overview of the internal mathematics that underlies Topic Models, and what that mathematics might imply for you, the modeler. While I'll explain a few things here, a more precise and technical explanation given by the inventor of the technique, David Blei, is available. Where there seems to be conflict between his explanation and mine, rest assured, his is correct!