What are weights and biases?
Weights and biases are numbers the model adjusts during training. Connections between units have weights; biases shift outputs slightly before activation.
“Learning” mostly means finding better values for millions or billions of parameters so loss decreases.
On mej7.com, the Weights section and Neural Network Lab show how matrix multiplies and activations change the signal — with demo numbers.