cousera-ml

Python port of the Coursera-Stanford Machine Learning Matlab code

How to use:

Just download or clone the repository, name your solution like the corresponding .m file but change the extension to .py and finally run:

python submit.py

Code design and organization

Same structure of the Matlab code ex1, ex2, etc folders with corresponding .py files instead of .m files. There should also be a test file per folder, ex: ex1/test_ex1.py.

Requirements

• numpy
• pytest (optional for testing)

Development Roadmap

• Implement quicklogin
• More testing
• Add templates for remaining exercises

Testing

Set your email as an environment variable with export COURSERA_EMAIL='your@email.com' and then run py.test

Contributing

1. Find a bug or feature you'd like to work on.
2. If you don't have one, create a free account on github <http://www.github.com>.
3. Set up your local development environment with git (Instructions <http://help.github.com/set-up-git-redirect>).
4. Fork the coursera-ml repository <http://www.github.com./elyase/coursera-ml> (Instructions <http://help.github.com/fork-a-repo/>).
5. Create a new working branch for your changes.
6. If possible make sure your patch includes a corresponding test.
7. Commit your changes and submit a pull request (Instructions <http://help.github.com/send-pull-requests/>).