Scikit-learn

Scikit-learn is an open-source machine learning library for Python that provides simple and efficient tools for data mining and data analysis. Built on NumPy, SciPy, and matplotlib, it offers a comprehensive collection of algorithms for classification, regression, clustering, dimensionality reduction, model selection, and preprocessing. The library features a consistent API design that enables easy experimentation with different algorithms through uniform interfaces. scikit-learn includes popular algorithms such as support vector machines, random forests, gradient boosting, k-means clustering, and principal component analysis. It provides robust model evaluation tools including cross-validation, grid search, and performance metrics. Widely adopted in industry and academia, scikit-learn serves as the foundation for many machine learning workflows due to its extensive documentation, active community support, and integration with the broader Python scientific ecosystem.