I would love to see an LW sequence on machine learning! I imagine that LW would have a lot of interesting things to say about the philosophical aspects of ML in addition to the practical aspects.

I'm not sure I'd be qualified to contribute much to such a sequence, since I am just an undergrad, but I did have an outline in mind for an intuitive introduction to MLE and EM. If people would find that interesting, I could certainly post it on LW once it was written up!

I'm fairly inexperienced in ML, so all the models I've worked with are simple enough that they've had conjugate priors. (I think it's really cool that Dirichlet priors can be used for something as complicated as an HMM, but I guess the HMM is still just a whole bunch of multinomials.) I'm less familiar with hierarchical models. What is an example of a model for which is it difficult to use conjugate priors? The only hierarchical process I've heard about is the Dirichlet process, and I was under the impression (based on the name) that it involved Dirichlet priors somewhere; is this incorrect? I have been meaning to read about hierarchical models, so if you know of any good tutorials or papers on them, I would very much appreciate a link!