Content overview: “NeuralCanvas Visual Builder”. Pick a layer type (Input, Dense, Dropout, BatchNormalization or Output), set units or dropout rate and activation (relu, sigmoid, tanh, softmax, linear), and click Add Layer to grow the stack. Reorder layers with up and down arrows on every card, delete with a single click, and watch a live WebGL-style canvas draw neurons and connections between each column as you build.
Set the input shape, pick your loss (sparsecategoricalcrossentropy, categoricalcrossentropy, binarycrossentropy, mse, mae), optimizer (Adam, SGD, RMSprop, AdamW) and learning rate, then hit Generate Keras Code to produce real, runnable TensorFlow/Keras Python you can copy to clipboard or download as a .py file. Export the layer stack as CSV for planning docs, back up the full schema as JSON, and a built-in Nova AI Guide button opens a conversational tutorial that walks through every layer type, cheat-sheet activations for classification, binary and regression, and workflow tips. The full version stays on the original page, which this listing opens directly.