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An Introduction to scikit-learn: Machine Learning in Python

Information on this tutorial can be found at the github repository:

This information will likely be updated often in the weeks before PyCon; please check back regularly.

Data Downloads

We will use several data sets for this tutorial. Because the wireless network at conferences can often be spotty, it would be a good idea to download these data sets before arriving at the conference. Please check at the github page above for details.

Installation Notes

This tutorial will require recent installations of numpy, scipy, matplotlib, scikit-learn, and ipython with ipython notebook. The last one is important: you should be able to type

ipython notebook

in your terminal window and see the notebook panel load in your web browser. Because Python 3 compatibility is still being ironed-out for these packages (we're getting close, I promise!) participants should plan to use Python 2.6 or 2.7 for this tutorial.

For users who do not yet have these packages installed, a relatively painless way to install all the requirements is to use a distribution such as Anaconda CE, which includes all of the requirements, works on Mac, Linux, and Windows, and can be downloaded and installed for free.