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Programming language: Go
Tags: Machine Learning    
Latest version: v0.2-alpha

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README

GoMind

Build Status GoDoc codecov Go Report Card License: GPL v3

Installation

go get github.com/surenderthakran/gomind

About

GoMind is a neural network library written entirely in Go. It only supports a single hidden layer (for now). The network learns from a training set using back-propagation algorithm.

Some of the salient features of GoMind are:

  • Supports following activation functions:
  • Smartly estimates ideal number of hidden layer neurons (if a count is not given during model configuration) for given input and output sizes.
  • Uses Mean Squared Error function to calculate error while back propagating.

Note: To understand the basic functioning of back-propagation in neural networks, one can refer to my blog here.

Usage

package main

import (
    "github.com/singhsurender/gomind"
)

func main() {
    trainingSet := [][][]float64{
        [][]float64{[]float64{0, 0}, []float64{0}},
        [][]float64{[]float64{0, 1}, []float64{1}},
        [][]float64{[]float64{1, 0}, []float64{1}},
        [][]float64{[]float64{1, 1}, []float64{0}},
    }

    mind, err := gomind.New(&gomind.ModelConfiguration{
        NumberOfInputs:                    2,
        NumberOfOutputs:                   1,
        NumberOfHiddenLayerNeurons:        16,
        HiddenLayerActivationFunctionName: "relu",
        OutputLayerActivationFunctionName: "sigmoid",
    })
    if err != nil {
        return nil, fmt.Errorf("unable to create neural network. %v", err)
    }

    for i := 0; i < 500; i++ {
        rand := rand.Intn(4)
        input := trainingSet[rand][0]
        output := trainingSet[rand][1]

        if err := mind.LearnSample(input, output); err != nil {
            mind.Describe(true)
            return nil, fmt.Errorf("error while learning from sample input: %v, target: %v. %v", input, output, err)
        }

        actual := mind.LastOutput()
        outputError, err := mind.CalculateError(output)
        if err != nil {
            mind.Describe(true)
            return nil, fmt.Errorf("error while calculating error for input: %v, target: %v and actual: %v. %v", input, output, actual, err)
        }

        outputAccuracy, err := mind.CalculateAccuracy(output)
        if err != nil {
            mind.Describe(true)
            return nil, fmt.Errorf("error while calculating error for input: %v, target: %v and actual: %v. %v", input, output, actual, err)
        }

        fmt.Println("Index: %v, Input: %v, Target: %v, Actual: %v, Error: %v, Accuracy: %v\n", i, input, output, actual, outputError, outputAccuracy)
    }
}

API Documentation

The documentation for various methods exposed by the library can be found at: https://godoc.org/github.com/surenderthakran/gomind


*Note that all licence references and agreements mentioned in the GoMind README section above are relevant to that project's source code only.