Neural Network Data Flow Visualization

Input Data

Click pixels to draw or use examples below

● Input Layer ● Hidden Layers ● Output Layer ━ Strong Connection ━ Weak Connection

Receives raw pixel data (0.0 to 1.0 values representing darkness/brightness)

Each connection has a weight (strength). Data is multiplied by these weights.

Neurons sum weighted inputs and "activate" if the sum exceeds a threshold

Hidden layers detect features and patterns in the data

Final classification - highest activated neuron is the prediction