Go Machine Learning

General Machine Learning library for Go.

Gorgonia is a library that helps facilitate machine learning in Go.

Easy to use Tensorflow bindings: simplifies the usage of the official Tensorflow Go bindings. Define computational graphs in Go, load and execute models trained in Python.

On-line Machine Learning in Go

Go package for OCR (Optical Character Recognition), by using Tesseract C++ library.

Fast, flexible, multi-threaded ensembles of decision trees for machine learning in pure Go.

Naive Bayesian Classification for Golang.

Multi-population, flexible, parallel genetic algorithm.

Neural Networks written in go

Recommendation & collaborative filtering engine

A feature-rich neural network library in Go.

Genetic Algorithms library written in Go / golang

partial port of scikit_learn to golang

Recommendation Algorithms library written in Go.

Bayesian text classifier with flexible tokenizers and storage backends for Go

Go bindings for Fast Artificial Neural Networks(FANN) library.

NEUGO: Neural Networks in Go

Genetic algorithm library for Go.

libsvm golang version derived work based on LIBSVM 3.14.

Plug-and-play, parallel Go framework for NeuroEvolution of Augmenting Topologies (NEAT).

Pattern recognition package in Go lang.

A multilayer perceptron network implemented in Go, with training via backpropagation.

EAGO: Evolutionary Algorithms in Go

liblinear bindings for Go

Go Scoring API for PMML.

A Deep Neural Network library written in Go.

Golang Neural Network.

Go implementation of the k-modes and k-prototypes clustering algorithms.

Various probability distributions, and associated methods.

Probability distribution functions. Bayesian inference. Written in pure Go.

This project aims to provide minimalistic machine learning algorithms in Go.