scikit-learn
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Introduction
scikit-learn is a free machine learning library for Python, featuring simple and efficient tools for data mining and data analysis.
Listed on
July 22, 2026
What is scikit-learn?
scikit-learn is an open-source machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.
How to use scikit-learn?
- Install scikit-learn via pip or conda, then import it in your Python code. The library provides a consistent interface for fitting models with the fit() method, predicting with predict(), and transforming data with transform(). Extensive documentation and tutorials are available on the official website.
Core features of scikit-learn
- Classification: Identifying which category an object belongs to.
- Regression: Predicting a continuous-valued attribute associated with an object.
- Clustering: Automatic grouping of similar objects into sets.
- Dimensionality reduction: Reducing the number of random variables to consider.
- Model selection: Comparing, validating and choosing parameters and models.
- Preprocessing: Feature extraction and normalization.
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