Scikit-learn, also known as sklearn, is a free and open-source machine learning library in Python. It provides a wide range of supervised and unsupervised learning algorithms, as well as tools for model fitting, data preprocessing, evaluation, and deployment. Initially developed by David Cournapeau as a Google Summer of Code project in 2007, it has since grown into a robust library supported by a large community of contributors. Key contributors who took leadership of the project and released the first public version in 2010 include Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, and Vincent Michel. Scikit-learn is a NumFOCUS fiscally sponsored project.
Scikit-learn offers a consistent API and integrates well with other Python libraries like NumPy, SciPy, and Matplotlib. Its functionality includes classification, regression, clustering, model selection, and preprocessing. It is used in various applications, including spam detection and predicting stock prices. Scikit-learn is available under the 3-Clause BSD license. As an open-source library, Scikit-learn is available for free. Installation is straightforward using pip or conda.
