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

go-featureprocessing alternatives and similar packages

Based on the "Machine Learning" category.
Alternatively, view go-featureprocessing alternatives based on common mentions on social networks and blogs.

• GoLearn

  9.7 5.9 go-featureprocessing VS GoLearn

  General Machine Learning library for Go.

• Gorgonia

  9.2 8.2 go-featureprocessing VS Gorgonia

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

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• tfgo

  8.3 5.6 go-featureprocessing VS tfgo

  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.

• gosseract

  8.1 5.3 go-featureprocessing VS gosseract

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

• goml

  7.9 0.0 go-featureprocessing VS goml

  On-line Machine Learning in Go

• gorse

  7.8 4.9 go-featureprocessing VS gorse

  A High Performance Recommender System Package based on Collaborative Filtering for Go.

• CloudForest

  7.4 0.0 go-featureprocessing VS CloudForest

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

• bayesian

  7.4 0.0 go-featureprocessing VS bayesian

  Naive Bayesian Classification for Golang.

• gago

  7.3 3.7 go-featureprocessing VS gago

  Multi-population, flexible, parallel genetic algorithm.

• gobrain

  6.8 2.1 go-featureprocessing VS gobrain

  Neural Networks written in go

• ocrserver

  6.6 0.3 go-featureprocessing VS ocrserver

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

• onnx-go

  6.1 1.3 go-featureprocessing VS onnx-go

  Go Interface to Open Neural Network Exchange (ONNX).

• go-deep

  6.1 0.0 go-featureprocessing VS go-deep

  A feature-rich neural network library in Go.

• sklearn

  6.0 0.8 go-featureprocessing VS sklearn

  partial port of scikit_learn to golang

• regommend

  6.0 0.0 go-featureprocessing VS regommend

  Recommendation & collaborative filtering engine

• go-galib

  5.7 0.0 go-featureprocessing VS go-galib

  Genetic Algorithms library written in Go / golang

• goRecommend

  5.3 0.0 go-featureprocessing VS goRecommend

  Recommendation Algorithms library written in Go.

• shield

  5.2 0.0 go-featureprocessing VS shield

  Bayesian text classifier with flexible tokenizers and storage backends for Go

• Goptuna

  5.1 8.9 go-featureprocessing VS Goptuna

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

• go-fann

  4.8 0.0 go-featureprocessing VS go-fann

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

• goga

  4.5 0.0 go-featureprocessing VS goga

  Genetic algorithm library for Go.

• libsvm

  4.3 0.0 go-featureprocessing VS libsvm

  libsvm golang version derived work based on LIBSVM 3.14.

• neat

  4.2 0.0 go-featureprocessing VS neat

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

• goscore

  4.2 0.0 go-featureprocessing VS goscore

  Go Scoring API for PMML.

• go-pr

  3.9 0.0 go-featureprocessing VS go-pr

  Pattern recognition package in Go lang.

• neural-go

  3.9 0.0 go-featureprocessing VS neural-go

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

• NEUGO

  3.8 0.0 go-featureprocessing VS NEUGO

  NEUGO: Neural Networks in Go

• golinear

  3.5 0.0 go-featureprocessing VS golinear

  liblinear bindings for Go

• fonet

  3.3 0.0 go-featureprocessing VS fonet

  A Deep Neural Network library written in Go.

• Varis

  3.1 0.0 go-featureprocessing VS Varis

  Golang Neural Network.

• EAGO

  2.9 0.0 go-featureprocessing VS EAGO

  EAGO: Evolutionary Algorithms in Go

• go-cluster

  2.9 0.0 go-featureprocessing VS go-cluster

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

• godist

  2.6 0.0 go-featureprocessing VS godist

  Various probability distributions, and associated methods.

• evoli

  2.3 2.4 go-featureprocessing VS evoli

  Genetic Algorithm and Particle Swarm Optimization library.

• probab

  2.0 0.0 go-featureprocessing VS probab

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

• GoMind

  1.5 0.0 go-featureprocessing VS GoMind

  A simplistic Neural Network Library in Go.

• randomforest

  1.4 0.0 go-featureprocessing VS randomforest

  Easy to use Random Forest library for Go.

• mlgo

  1.0 0.0 go-featureprocessing VS mlgo

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

• ddt

  0.7 5.8 go-featureprocessing VS ddt

  Dynamic decision tree, create trees defining customizable rules.

Do you think we are missing an alternative of go-featureprocessing or a related project?

Popular Comparisons

• GoLearn
  vs
  Gorgonia
• GoLearn
  vs
  goml
• GoLearn
  vs
  neural-go
• Gorgonia
  vs
  goml
• regommend
  vs
  GoLearn

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