CS 1678/2078 Introduction to Deep Learning (Fall 2024)

Introductory course to deep learning at the University of Pittsburgh

Class is held MW 11:00-12:15 in SENSQ 5505.

syllabus

This course will cover the basics of modern deep neural networks. The first part of the course will introduce function approximation, neural network architectures, activation functions, and operations. It will present different loss functions and describe how training is performed via backpropagation. In the second part, the course will describe specific types of neural networks, e.g. convolutional, recurrent, and transformers, as well as their applications in computer vision and natural language processing. The course will also briefly discuss foundation models, self-supervised and deep reinforcement learning, and generation approaches.

Instruction Team:

  • Scott Jordan (Instructor)
    Email: scott jordan pitt edu
    Office hours: M 12:15-1:15 in SENSQ 6105

  • TBA

The course content will be posted on Canvas. Check there for the most up-to-date information.