PyData Seattle 2015 Scikit-learn Tutorial

Instructor: Jake VanderPlas

email: jakevdp@uw.edu
twitter: @jakevdp
github: jakevdp

This repository will contain files and other info associated with my PyData Seattle 2015 scikit-learn tutorial.

Installation Notes

This tutorial requires the following packages:

Python version 2.6-2.7 or 3.3-3.4
numpy version 1.5 or later: http://www.numpy.org/
scipy version 0.10 or later: http://www.scipy.org/
matplotlib version 1.3 or later: http://matplotlib.org/
scikit-learn version 0.14 or later: http://scikit-learn.org
ipython version 2.0 or later, with notebook support: http://ipython.org
seaborn version 0.5 or later

The easiest way to get these is to use the conda environment manager. I suggest downloading and installing miniconda.

Once this is installed, the following command will install all required packages in your Python environment:

$ conda install numpy scipy matplotlib scikit-learn ipython-notebook seaborn

Alternatively, you can download and install the (very large) Anaconda software distribution, found at https://store.continuum.io/.

Downloading the Tutorial Materials

I would highly recommend using git, not only for this tutorial, but for the general betterment of your life. Once git is installed, you can clone the material in this tutorial by using the git address shown above:

git clone git://github.com/jakevdp/sklearn_pydata2015.git

If you can't or don't want to install git, there is a link above to download the contents of this repository as a zip file. I may make minor changes to the repository in the days before the tutorial, however, so cloning the repository is a much better option.

Notebook Listing

You can view the tutorial materials using the excellent nbviewer service.

Note, however, that you cannot modify or run the contents within nbviewer. To modify them, first download the tutorial repository, change to the notebooks directory, and run ipython notebook. You should see the list in the ipython notebook launch page in your web browser. For more information on the IPython notebook, see http://ipython.org/notebook.html

Note also that some of the code in these notebooks will not work outside the directory structure of this tutorial, so it is important to clone the full repository if possible.