abstract: These lectures will build on basics of information theory and statistical decision theory to formalize the problem of learning representations of the data for machine learning tasks, with a focus on classification. We will then describe learning and inference techniques using deep neural networks, including optimization and regularization.
There are no formal prerequisites other than graduate standing in a mathematics, engineering or science field, which assumes fluency with probability, calculus, linear algebra, and differential equations.