GoNN
A Go implementation of neural networks including BackPropagation, RBF, and Perceptron networks with parallel processing capabilities.
What is GoNN?
GoNN is a neural network implementation written in Go that provides BackPropagation Network (BPNN), Radial Basis Function Network (RBF), and Perceptron Network (PCN) architectures. It solves the problem of implementing and training neural networks directly in Go without requiring external machine learning libraries or Python dependencies.
Go developers who want to implement neural networks in their applications, researchers prototyping neural network algorithms in Go, and anyone interested in understanding neural network implementations in a compiled language.
Developers choose GoNN for its pure Go implementation, support for multiple neural network architectures, and built-in parallel processing capabilities through goroutines, making it a lightweight alternative to larger machine learning frameworks.
Overview
GoNN is an implementation of Neural Network in Go Language, which includes BPNN, RBF, PCN
Use Cases
Best For
- Implementing neural networks in Go applications
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