General Machine Learning library for Go.

An offline recommender system backend based on collaborative filtering written in Go.

graph-based computational library like Theano for Go that provides primitives for building various machine learning and neural network algorithms.

A CLI tool to transpile trained classic ML models into a native Go code with zero dependencies, written in Python with Go language support.

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

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.

An evolutionary optimization library.

Naive Bayesian Classification for Golang.

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

Go Interface to Open Neural Network Exchange (ONNX).

A simple OCR API server, seriously easy to be deployed by Docker and Heroku.

An accelerated Machine Learning framework for Go.

Neural Networks written in go.

A feature-rich neural network library in Go.

Huggingface transformer pipelines for golang with onnxruntime.

Recommendation & collaborative filtering engine.

Bayesian optimization framework for black-box functions written in Go. Everything will be optimized.

Genetic algorithm library for Go.

Recommendation Algorithms library written in Go.

Genetic Algorithms library written in Go / golang.

Bayesian text classifier with flexible tokenizers and storage backends for Go.

Fast and convenient feature processing for low latency machine learning in Go.

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

Go Scoring API for PMML.

A simplistic Neural Network Library in Go.

A Deep Neural Network library written in Go.

Neural Network for Go.

libsvm golang version derived work based on LIBSVM 3.14.

Multilayer perceptron network implemented in Go, with training via backpropagation.

Pattern recognition package in Go lang.

Golang Neural Network.

Easy to use Random Forest library for Go.

liblinear bindings for Go.

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

Various probability distributions, and associated methods.

Dynamic decision tree, create trees defining customizable rules.

Genetic Algorithm and Particle Swarm Optimization library.

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