goneural

README

goneural

Go Report Card: report — static checks for this module.

Repository: github.com/BrandonKS05/goneural

A small feedforward neural network library in Go, implemented without a heavyweight ML stack. Matrix operations use the matrigo module (see go.mod). Model save/load uses Protocol Buffers.

Module

github.com/BrandonKS05/goneural

Import the goneural package (library code lives in the goneural subdirectory):

import "github.com/BrandonKS05/goneural/goneural"

Pin a version (recommended):

go get github.com/BrandonKS05/goneural/goneural@v1.0.0

Features

• Configurable layers, activations (sigmoid, ReLU, identity; softmax not implemented), and mean squared error loss
• Forward pass (Predict), training with backpropagation
• Optimizers: stochastic gradient descent, mini-batch gradient descent, batch gradient descent
• Optional genetic operators: copy, crossover, Gaussian mutation
• Serialize and deserialize networks to disk (weights, biases, layer metadata)

Usage

g := goneural.New(
	0.1,
	goneural.MSE(),
	goneural.Layer{Nodes: 2},
	goneural.Layer{Nodes: 4, Activator: goneural.Sigmoid()},
	goneural.Layer{Nodes: 1},
)

g.Train(goneural.SGD(), goneural.DataSet{
	{Inputs: []float64{1, 0}, Targets: []float64{1}},
	{Inputs: []float64{0, 1}, Targets: []float64{1}},
	{Inputs: []float64{1, 1}, Targets: []float64{0}},
	{Inputs: []float64{0, 0}, Targets: []float64{0}},
}, 5000)

g.Predict([]float64{1, 1})

Save and load (filename extension is up to you; .goneural matches the project name):

g.Save("model.goneural")
g, err := goneural.Load("model.goneural")

Examples

• examples/xor — XOR with a small MLP
• examples/perceptron — single perceptron demo

Requirements

Go 1.21+ (see go.mod).

Clone

git clone https://github.com/BrandonKS05/goneural.git

License

See LICENSE in this repository.