Every neural-network tutorial I tried threw equations at me before I ever saw what was actually happening. I wanted the reverse: watch the activations flow forward, watch the loss bars shrink, watch backprop push gradients right-to-left across the layers. So I built it. Here's a neural network that trains itself in front of you 👇 What you're actually seeing Forward pass — particles flow left → right as activations propagate through the layers. Loss — bars drop each epoch, and the output neurons