Original Summary

I recently finished building a small XOR neural network entirely using Python and NumPy. It's a 2 → 3 → 1 architecture trained with manually implemented backpropagation and gradient descent. Rather than just sharing the code, I wanted the repository to explain the entire process. So I added mathematical derivations, architecture diagrams, loss visualizations, trained weights and a collection of editable Excalidraw diagrams. The network reaches 4/4 correct classifications on XOR after 5,000 training epochs. GitHub: https://github.com/Vaibh37/Neural-Network It's an open-source educational project, not a production ML model. I'd love feedback on the documentation and what would make it more useful for someone learning neural networks. If you find it useful, consider starring the repository!   submitted by   /u/PanelReader [link]   [comments]

  • 情报分类：技术学习与提效
  • 分类依据：内容涉及技术、AI、软件工具或工程实践
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/10/19 00:08:51