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Scikit-learn
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Scikit-learn

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Scikit-learn is an open source machine learning library for the Python programming language.

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Machine Learning Library

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Ease of use
7.6
Features & Functionality
7.6
Advanced Features
7.7
Integration
7.7
Performance
7.5
2.5
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7.5
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Scikit-learn 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.

7.6
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Scikit-learn
5 (100%) 3 ratings

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.

Classification : Identifying to which category an object belongs to Applications: Spam detection, Image recognition. Algorithms: SVM, nearest neighbors, random forest.
Regression : Predicting a continuous-valued attribute associated with an object. Applications: Drug response, Stock prices. Algorithms: SVR, ridge regression.
Clustering :Automatic grouping of similar objects into sets. Applications: Customer segmentation, Grouping experiment outcomes. Algorithms: k-Means, spectral clustering, mean-shift.

Scikit-learn

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Ease of use
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