Python machine-learning library. Installing SciPy/Windows - These are instructions for installing the full SciPy stack.
For installing individual packages, such as NumPy and SciPy, see Individual binary and source packages below. Scientific Python distributions For most users, especially on Windows and Mac, the easiest way to install the packages of the SciPy stack is to download one of these Python distributions, which includes all the key packages: Anaconda: A free distribution for the SciPy stack. Supports Linux, Windows and Mac.Enthought Canopy: The free and commercial versions include the core SciPy stack packages. Python machine learning packages. Hi, I am one of the developers of scikit-learn .
The project has recently gained steam and is moving fast thanks to new contributors. The design goals are: wide coverage of cutting edge algorithms with a simple to use unified APIa permissive license for embedding (simplified BSD) and low dependencies requirements (numpy + scipy)optimized yet maintainable implementation using cython when usefulscalable algorithms with dense and sparse representations of the features (useful for text classification of with ten of thousands of samples with ~100 000 features for instance).tooling to perform cross validation & performance evaluation across all algorithms that respect the API (duck typing) well tested >= 500 tests that run under 15s with a coverage of ~85% and improving (see our buildbot)well documented too with worked examples (could still be very much improved though)readable source code respecting PEP8 conventions Current limitations: MLPY - high-performance Python library for predictive modeling.
Pragmatic Classification with Python. Python and Machine Learning. What are the best open source machine learning libraries written in Python. User guide: contents — scikit-learn 0.13.1 documentation.