This repository contains interactive Jupyter Notebook tutorials on neural networks and deep learning, written from scratch using NumPy without relying on major ML frameworks. Projects focus on visualizing core concepts like gradient descent, activation functions, and classification boundaries. Content is designed to complement Medium articles and serve as a hands-on learning resource for understanding the mathematics behind deep networks.