Elementary Gaussian Processes in Python

Gaussian processes are so hot right now, but I haven’t seen examples of the very basic computations you do when you’re “using Gaussian processes”. There are tons of packages that do these computations for you — scikit- learn, GPy, pygp —but I wanted to work through some examples using, and showing, the basic linear algebra involved. Below is what I came up with, as incarnated in an IPython notebook showing a few simple analyses.

This post is also a pilot for embedding IPython notebooks on this blog. Overall it was pretty straightforward, though I had to insert a few small tweaks to get the layout to work right — definitely worth the effort, though! I haven’t really used an IPython notebook before but I gotta say it worked really well here. I generally prefer the console for getting work done, but it’s a really nice format for pedagogy.

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Later: scipy.stats Cheat Sheet

Earlier: Announcing: worklog-tools, for automating tedious CV activities

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