Showing 8 of 8 projects
A comprehensive .NET framework for machine learning, computer vision, statistics, and scientific computing.
A comprehensive Swift framework providing AI/ML algorithms including neural networks, SVMs, PCA, genetic algorithms, and MDPs with GPU acceleration support.
A comprehensive Swift framework providing AI/ML algorithms including neural networks, SVMs, genetic algorithms, and MDPs with GPU acceleration.
A Python library for structured learning and prediction with max-margin methods and a scikit-learn compatible interface.
A Swift library providing neural networks, machine learning algorithms, and AI data structures for iOS and macOS development.
Ruby interface to LIBLINEAR for machine learning classification and regression tasks using SWIG bindings.
A Go port of LIBSVM 3.14, providing support vector machine (SVM) algorithms for classification and regression.
A fast and versatile implementation of support vector machines with integrated hyper-parameter selection and support for multiple learning scenarios.
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