Backpropagation, attention & inference — how neural networks and transformer models actually compute.
Train a real feedforward classifier in your browser and trace every forward pass and backprop update by hand.
Run a real miniature transformer through prefill and autoregressive decoding, with temperature/top-k/top-p sampling and a live KV cache.
Open up a real trained transformer block and inspect every operation — embedding, attention, residual and feed-forward — on one token.