ptobarra / machine_learning

Python coded examples and documentation of machine learning algorithms.

machine_learning

This repo contains a collection of IPython notebooks detailing various machine learning algorithims. In general, the mathematics follows that presented by Dr. Andrew Ng's Machine Learning course taught at Stanford University (materials available from [ITunes U] (http://www.apple.com/education/itunes-u/), Stanford Machine Learning), Dr. Tom Mitchell's course at Carnegie Mellon (materials avialable here), and Christopher M. Bishop's "Pattern Recognition And Machine Learning". Unless otherwise noted, the Python code is orginal and any errors or ommissions should be attribued to me and not the aforemention authors.

Each ipynb provides a list of the pertinent reading material. It is suggested that the material be read in the order provided.

If you do not have IPython installed or Notebook configured (why not?) the src directory has .py versions of the notebook files and some of the PDF output files are in this repository's Downloads section. However, they are not always as updated as the ipynb files.

Python Version 2.7.2 IPython Version 0.13