go-deep
A Go library implementing feedforward/backpropagation neural networks with support for multiple activation functions, solvers, and classification modes.
What is go-deep?
go-deep is a pure Go implementation of feedforward and backpropagation neural networks, designed for educational and small-scale machine learning tasks. It provides a straightforward API for building and training neural networks without GPU acceleration, making it suitable for prototyping and learning.
Go developers and students interested in understanding neural network fundamentals or prototyping small-scale machine learning models without GPU dependencies.
Developers choose go-deep for its simplicity, clear modeling of neurons and synapses, and pure Go implementation that avoids GPU complexity, making it ideal for learning and lightweight applications.
Overview
Artificial Neural Network
Use Cases
Best For
- Learning neural network fundamentals through a clear, neuron-and-synapse-based implementation in Go.
- Prototyping small-scale machine learning models like binary or multi-class classifiers without GPU requirements.
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