Hi r/MachineLearning,

I built OpenTrainDNN, a browser-based tool designed to visually show how backpropagation and neural network training actually work step-by-step.

Why I built it

While there are theoretical guides on backpropagation, it can be hard to build an intuitive mental model without seeing weight updates, activations, and gradients evolve visually in real-time. I wanted a zero-setup, lightweight tool to experiment with these mechanics instantly.

Key Features

• Zero Dependencies / No Installation: Runs completely in the browser via GitHub Pages.
• Real-time Backpropagation: Visualizes forward passes, loss calculation, gradient computation, and weight updates interactively.
• Interactive Parameters: Adjust learning rates, inputs, and network structure to observe convergence or divergence live.

I would love to get your feedback on the layout, visualization accuracy, or features you'd like to see added to make it more useful for learners and educators!