neural-net-ruby
A lightweight feedforward neural network with resilient backpropagation (Rprop), implemented in pure Ruby with no external dependencies.
What is neural-net-ruby?
Neural Net (in Ruby) is a lightweight, educational implementation of a feedforward neural network using the resilient backpropagation (Rprop) training algorithm. It provides a simple, dependency-free way to understand neural network fundamentals in Ruby, with examples for classification, regression, and OCR tasks. The project is designed for learning and experimentation rather than production use.
Ruby developers and students interested in learning how neural networks work from scratch, or those seeking a minimal, readable implementation for educational purposes.
Developers choose this for its simplicity, pure Ruby implementation with no dependencies, and clear examples that demystify neural network concepts. It offers a faster training alternative to basic backpropagation while remaining accessible and easy to modify.
Overview
A neural network, written in Ruby
Use Cases
Best For
- Learning neural network fundamentals in Ruby
- Experimenting with Rprop training algorithms
Related Projects
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
