This repository provides mathematical derivations and Python code implementations of concepts from the Deep Learning textbook by Goodfellow, Bengio, and Courville. It covers topics including linear algebra, probability, deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and generative models. The implementations use numpy as the primary library, allowing readers to understand the underlying mechanics of deep learning algorithms.