Showing 12 of 12 projects
A fast Support Vector Machine (SVM) library that leverages GPUs and multi-core CPUs for high-performance machine learning.
A Ruby machine learning library with a Scikit-Learn-like interface for classification, regression, clustering, and dimensionality reduction.
A pure Java machine learning library with no external dependencies, offering a wide collection of algorithms and parallel execution support.
A fast, robust Python library to detect offensive language in text using a machine learning model.
A TypeScript machine learning library for the web and Node.js with a simple, consistent API.
A Java port of LIBLINEAR for large-scale regularized linear classification, regression, and outlier detection.
Ruby language bindings for the LIBSVM library, enabling support vector machine (SVM) classification and regression in Ruby.
A high-performance, large-scale statistical machine learning library written in Common Lisp.
A fast and versatile implementation of support vector machines with integrated hyper-parameter selection and support for multiple learning scenarios.
Torch7 library providing SVM implementations including SGD-based methods and LIBLINEAR wrapper.
Native Julia implementations of standard SVM algorithms, including Pegasos and Dual Coordinate Descent.
An open-source JavaScript library implementing machine learning algorithms for educational purposes with interactive visualizations.
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