Neural Network 101

Built to make the math click. Most introductions to neural networks ask you to trust the math. Loss curves go down, accuracy goes up, but the inner workings stay hidden behind libraries. This is a transparent, hands-on playground. Every node, edge, gradient and step of backprop is rendered. You can pause time, drag a weight, delete a neuron, and watch the decision boundary react.