scikit-learn

Scikit-learn is a crucial open source tool for engineering teams focused on machine learning and data analysis. It simplifies the implementation of machine learning algorithms, making it accessible for data scientists and ML engineers. With over 65,000 stars and a steady growth of 1,036 stars in 96 days, scikit-learn demonstrates strong community support and maturity, making it a production-ready solution. However, it may not be the best choice for deep learning tasks or scenarios requiring highly specialised models, where frameworks like TensorFlow or PyTorch might be more suitable.

Scikit-learn is a strong choice when teams need a reliable, production-ready solution for traditional machine learning tasks such as classification, regression, and clustering. Teams should consider alternatives when their projects require deep learning capabilities or extensive customisation.

Data scientists and ML engineers typically use scikit-learn for developing predictive models and conducting data analysis. It is commonly integrated into products and systems that require machine learning functionalities, such as recommendation engines and data-driven applications.

Latest commit: 2026-02-13. Over the past 97 days, this repository gained 1.0k stars (+1.6% growth). Activity data is based on daily RepoPi snapshots of the GitHub repository.