Hi everyone, I've been working on this for the last few days. I was studying neural networks and I wanted to understand backprop for real, so I decided to make one from scratch, without ML libraries. It's a desktop app (Python + NumPy) where a small neural network learns to read handwritten digits, and you can watch it while it trains and see the neurons light up when you draw a digit. There's also a tab with the math of each layer. And you can break it on purpose... switch off neurons or add noise and see how much the accuracy goes down. If something is not clear you press F1 and click it, and it gets explained. There's also an assistant you can ask things like "what should I do now?", it looks at your training and suggests what to try (no AI there, just a small search engine in NumPy and a few rules). It's free and open source (MIT), in English and Italian. To try it pip install neural-network-digits, or on Windows download the zip and double-click start.bat. Most of the code was written with Claude Code (AI), the idea and what goes in every tab are mine. https://github.com/dev-luigi/neural-network-digits The app has 5 tabs and a lot of knobs: is it too much for a beginner at the start? What would you simplify?   submitted by   /u/No-Brain-1655 [link]   [comments]