Showing 10 of 82 projects
A Go module implementing multi-layer neural networks for machine learning tasks.
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.
A fungal image classification project using ResNet to identify mushroom species from citizen science and expert sources.
A Ruby gem for scoring predictive models using PMML, supporting decision trees, naive Bayes, logistic regression, random forests, and gradient boosted trees.
A pattern recognition library for Go providing classification, clustering, and feature extraction algorithms.
A Clojure library providing machine learning algorithms with simple APIs for data preprocessing and modeling.
A JRuby gem providing Ruby interfaces for Weka's machine learning and data mining algorithms.
A JavaScript library implementing logistic regression and C4.5 decision tree algorithms for machine learning in the browser and Node.js.
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