This repository contains Jupyter notebooks that accompany the book Grokking Deep Learning, providing hands-on code examples for learning neural network fundamentals. The materials cover core deep learning topics including forward propagation, gradient descent, backpropagation, regularization, activation functions, and convolutional neural networks.