Lec 01. Introduction to Deep Learning

This introductory lecture covers the fundamentals of deep learning, including neural network architectures built from linear transformations and nonlinearities, differential programming paradigms using gradient-based optimization, and the historical evolution of the field from perceptrons to modern large-scale models. The Show more