Deep-Learning

Understanding Multi-Layer Perceptrons, network depth, and their theoretical capabilities as universal function approximators.

Deriving backpropagation using the chain rule. With a working Python implementation.

Building a minimal autograd engine in C++ to understand automatic differentiation from the ground up.