Gradient descent, how neural networks learn | Deep Learning Chapter 2

Gradient Descent explains how neural networks learn by iteratively adjusting weights and biases to minimize a cost function, while showing that high classification accuracy can still reflect memorization rather than genuine pattern recognition.