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https://github.com/jakevdp/sklearn_pycon2014

Repository containing files for my PyCon 2014 scikit-learn tutorial.
https://github.com/jakevdp/sklearn_pycon2014

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Repository containing files for my PyCon 2014 scikit-learn tutorial.

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README 

        
# PyCon 2014 Scikit-learn Tutorial



**Note: for updated tutorial content, please see http://github.com/jakevdp/sklearn_tutorial/**



*Instructor: Jake VanderPlas*



- email: 

- twitter: [@jakevdp](https://twitter.com/jakevdp)

- github: [jakevdp](http://github.com/jakevdp)



This repository will contain files and other info associated with my PyCon

2014 scikit-learn tutorial.



## Video

The video is available on PyVideo: [Exploring Machine Learning with Scikit-Learn](http://pyvideo.org/video/2561/exploring-machine-learning-with-scikit-learn)



## 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 package such as

[Anaconda](http://www.continuum.io/downloads "Anaconda"), which can be

downloaded and installed for free.



## 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_pycon2014.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

These notebooks in this repository can be statically viewed using the

excellent [nbviewer](http://nbviewer.ipython.org) site.  They will not

be able to be modified within nbviewer.  To modify them, first download

the tutorial repository, change to the notebooks directory, and type

``ipython notebook``.  You should see the list in the ipython notebook

launch page in your web browser.



- [00_Preliminaries.ipynb](http://nbviewer.ipython.org/urls/raw.github.com/jakevdp/sklearn_pycon2014/master/notebooks/00_Preliminaries.ipynb)

- [01_basics.ipynb](http://nbviewer.ipython.org/urls/raw.github.com/jakevdp/sklearn_pycon2014/master/notebooks/01_basics.ipynb)

- [02_data_representation.ipynb](http://nbviewer.ipython.org/urls/raw.github.com/jakevdp/sklearn_pycon2014/master/notebooks/02_data_representation.ipynb)

- [03_basic_principles.ipynb](http://nbviewer.ipython.org/urls/raw.github.com/jakevdp/sklearn_pycon2014/master/notebooks/03_basic_principles.ipynb)

- [04_supervised_in_depth.ipynb](http://nbviewer.ipython.org/urls/raw.github.com/jakevdp/sklearn_pycon2014/master/notebooks/04_supervised_in_depth.ipynb)

- [05_unsupervised_in_depth.ipynb](http://nbviewer.ipython.org/urls/raw.github.com/jakevdp/sklearn_pycon2014/master/notebooks/05_unsupervised_in_depth.ipynb)

- [06_validation.ipynb](http://nbviewer.ipython.org/urls/raw.github.com/jakevdp/sklearn_pycon2014/master/notebooks/06_validation.ipynb)



Note 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.