Varis alternatives and similar packages

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

GoLearn

9.6 0.0 Varis VS GoLearn

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gorse

9.4 7.1 Varis VS gorse

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InfluxDB - Power Real-Time Data Analytics at Scale

Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

Promo www.influxdata.com

Gorgonia

9.1 2.8 Varis VS Gorgonia

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

8.4 6.7 Varis VS gosseract

Go package for OCR (Optical Character Recognition), by using Tesseract C++ library
m2cgen

8.4 0.0 Varis VS m2cgen

Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies
tfgo

8.3 1.5 Varis VS tfgo

Tensorflow + Go, the gopher way
envd

8.0 9.0 Varis VS envd

🏕️ Reproducible development environment
goml

7.9 0.0 Varis VS goml

On-line Machine Learning in Go (and so much more)
gago

7.3 0.0 Varis VS gago

:four_leaf_clover: Evolutionary optimization library for Go (genetic algorithm, partical swarm optimization, differential evolution)
bayesian

7.2 2.3 Varis VS bayesian

Naive Bayesian Classification for Golang.
CloudForest

7.1 0.0 Varis VS CloudForest

Ensembles of decision trees in go/golang.
ocrserver

7.0 0.0 Varis VS ocrserver

A simple OCR API server, seriously easy to be deployed by Docker, on Heroku as well
onnx-go

6.8 2.3 Varis VS onnx-go

onnx-go gives the ability to import a pre-trained neural network within Go without being linked to a framework or library.
gobrain

6.7 0.0 Varis VS gobrain

Neural Networks written in go
go-deep

6.6 3.5 Varis VS go-deep

Artificial Neural Network
sklearn

6.0 0.0 Varis VS sklearn

bits of sklearn ported to Go #golang
regommend

5.9 0.0 Varis VS regommend

Recommendation engine for Go
go-galib

5.5 0.0 Varis VS go-galib

Genetic Algorithms library written in Go / golang
Goptuna

5.5 6.4 Varis VS Goptuna

A hyperparameter optimization framework, inspired by Optuna.
goRecommend

5.3 0.0 Varis VS goRecommend

Collaborative Filtering (CF) Algorithms in Go!
goga

5.3 0.0 Varis VS goga

Golang Genetic Algorithm
shield

5.2 0.0 Varis VS shield

Bayesian text classifier with flexible tokenizers and storage backends for Go
go-fann

4.6 0.0 Varis VS go-fann

Go bindings for FANN, library for artificial neural networks
goscore

4.4 0.0 Varis VS goscore

Go Scoring API for PMML
neat

4.2 0.0 Varis VS neat

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

4.1 0.0 Varis VS fonet

fonet is a deep neural network package for Go.
go-featureprocessing

4.1 5.2 Varis VS go-featureprocessing

🔥 Fast, simple sklearn-like feature processing for Go
libsvm

4.0 0.0 Varis VS libsvm

libsvm go version
NEUGO

3.8 0.0 Varis VS NEUGO

NEUGO: Neural Networks in Go
go-pr

3.8 0.0 Varis VS go-pr

Pattern recognition package in Go lang.
neural-go

3.7 0.0 Varis VS neural-go

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

3.7 0.0 Varis VS GoMind

A simplistic Neural Network Library in Go
golinear

3.4 0.0 Varis VS golinear

liblinear bindings for Go
go-cluster

3.2 0.0 Varis VS go-cluster

k-modes and k-prototypes clustering algorithms implementation in Go
EAGO

2.9 0.0 Varis VS EAGO

EAGO: Evolutionary Algorithms in Go
godist

2.8 0.0 Varis VS godist

Probability distributions and associated methods in Go
randomforest

2.8 2.6 Varis VS randomforest

Random Forest implementation in golang
evoli

2.8 0.0 Varis VS evoli

Genetic Algorithm and Particle Swarm Optimization
ddt

2.3 0.0 Varis VS ddt

Golang Dynamic Decision Tree
probab

2.0 0.0 Varis VS probab

Automatically exported from code.google.com/p/probab
mlgo

1.2 0.0 Varis VS mlgo

Automatically exported from code.google.com/p/mlgo

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README

Varis

Neural Networks with GO

About Package

Some time ago I decided to learn Go language and neural networks. So it's my variation of Neural Networks library. I tried to make library for programmers (not for mathematics).

For now Varis is 0.1 version.

I would be happy if someone can find errors and give advices. Thank you. Artem.

Main features

All neurons and synapses are goroutines.
Golang channels for connecting neurons.
No dependencies

Installation

go get github.com/Xamber/Varis

Usage

package main

import (
    "github.com/Xamber/Varis"
)

func main() {
    net := varis.CreatePerceptron(2, 3, 1)

    dataset := varis.Dataset{
        {varis.Vector{0.0, 0.0}, varis.Vector{1.0}},
        {varis.Vector{1.0, 0.0}, varis.Vector{0.0}},
        {varis.Vector{0.0, 1.0}, varis.Vector{0.0}},
        {varis.Vector{1.0, 1.0}, varis.Vector{1.0}},
    }

    trainer := varis.PerceptronTrainer{
        Network: &net,
        Dataset: dataset,
    }

    trainer.BackPropagation(10000)
    varis.PrintCalculation = true

    net.Calculate(varis.Vector{0.0, 0.0}) // Output: [0.9816677167418877]
    net.Calculate(varis.Vector{1.0, 0.0}) // Output: [0.02076530509106318]
    net.Calculate(varis.Vector{0.0, 1.0}) // Output: [0.018253250887023762]
    net.Calculate(varis.Vector{1.0, 1.0}) // Output: [0.9847884089930481]
}