Linear Models
Showing 7 of 7 projects
A comprehensive collection of machine learning algorithms implemented exclusively in NumPy for educational purposes and prototyping.
A high-performance, easy-to-use, and scalable machine learning package for linear models, factorization machines, and field-aware factorization machines.
A Go machine learning library with online learning capabilities and a variety of implemented models.
A Julia package for fitting linear and generalized linear mixed-effects models with maximum likelihood estimation.
A framework for building scalable machine learning models in Hadoop using the Scalding DSL.
A Clojure library for machine learning and statistical inference designed for production deployment and composable algorithms.
Ruby interface to LIBLINEAR for machine learning classification and regression tasks using SWIG bindings.
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