scikit-learn is a Python module for machine learning built on top of SciPy. It features various classification, regression and clustering algorithms including support vector machines, logistic regression, naive Bayes, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

• Simple and efficient tools for data mining and data analysis
• Accessible to everybody, and reusable in various contexts
• Built on NumPy, SciPy, and matplotlib
• Open source, commercially usable - BSD license

Information

• Website: http://scikit-learn.org/stable/
• GitHub: https://github.com/scikit-learn/scikit-learn
• Installation: http://scikit-learn.org/dev/install.html
• Documentation: http://scikit-learn.org/stable/documentation.html
• Examples: http://scikit-learn.org/stable/auto_examples/index.html