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2 changes: 1 addition & 1 deletion README.md
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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](http://www.cs.cmu.edu/~tom/10701_sp11/)), 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.
This repo contains a collection of IPython notebooks detailing various machine learning algorithms. 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 available [here](http://www.cs.cmu.edu/~tom/10701_sp11/)), and Christopher M. Bishop's "Pattern Recognition And Machine Learning". Unless otherwise noted, the Python code is original and any errors or omissions should be attributed to me and not the aforementioned authors.

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

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