I finally had a chance to do something I’ve been meaning to do for a long time: post some notebooks on machine learning on GitHub. IPython notebooks are a great way to mix text, math, and code. I’ve been writing ipython notebooks for a while to teach myself some machine learning concepts; there’s no better … More ipython notebooks on machine learning
Deepmind built an AI that masters Go. How did they do it? A technical introduction. … More 5 easy pieces: How Deepmind mastered Go
In the last post I showed how to fit a Bayesian hierarchical model in R to estimate experimental parameters. Our main data analysis pipeline uses Matlab, and we’d like to integrate these two environments for the purpose of analysis. The example involved JAGS, which does have a direct Matlab interface in addition to the more common R one, but more … More Calling R from Matlab – flat file communication
By far the most popular post on this blog is a review of several Python integrated development environments (IDEs) geared toward science. Coming from a Matlab background, it’s natural to search for something Matlab-like to replace it – an IDE with integrated editor, code execution, plotting, benchmarking, file management, etc. An increasingly attractive alternative is the IPython Notebook. The ipython Notebook … More Scientific Python in the browser: ipython notebook
Love and happiness It can make you do right, It can make you do wrong It can make you come home early It can make you stay out all night long I went to a LA machine learning meetup last week featuring Jon Morra from eHarmony, where he highlighted some of the uses of machine learning in their online dating platform. … More Machine learning in online dating
