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 way to learn than to try to explain something to someone else.
I posted two notebooks to start with: one on contextual bandits, and another on fitting maximum entropy models by persistent contrastive divergence. I’ve got a couple more in the bank, and several more in various states of disarray that I hope to clean up and post.
Stay tuned for more!
3 responses to “ipython notebooks on machine learning”
I am very new to this ML thing. You have given two notebook implementations here. For what kind of audiance these examples are suitable kindly let us know.
Great stuff, keep it going!
Thanks, I will!