numpy-ml is a growing collection of machine learning models, algorithms, and tools written exclusively in NumPy and the Python standard library.
The purpose of the project is to provide reference implementations of common machine learning components for rapid prototyping and experimentation. With that in mind, don't just read the docs -- read the source!
This documentation is under development!
We're working to expand our coverage. During this time there are likely to be typos, bugs, and poorly-worded sections. If you encounter any of the above, please file an issue or submit a pull request!
.. toctree:: :maxdepth: 3 :hidden: numpy_ml.hmm numpy_ml.gmm numpy_ml.lda numpy_ml.ngram numpy_ml.bandits numpy_ml.rl_models numpy_ml.nonparametric numpy_ml.factorization numpy_ml.trees numpy_ml.neural_nets numpy_ml.linear_models numpy_ml.preprocessing numpy_ml.utils
This software is provided as-is: there are no guarantees that it fits your purposes or that it is bug-free. Use it at your own risk!