Fall 2020 CS 498 Introduction to Deep Learning

Quick links: schedule, Compass2g (grades), Piazza (announcements, discussion board), course policies,
lecture videos

This course will provide an elementary hands-on introduction to neural networks and deep learning. Topics covered will include: linear classifiers; multi-layer neural networks; back-propagation and stochastic gradient descent; convolutional neural networks and their applications to computer vision tasks like object detection and dense image labeling; recurrent neural networks and state-of-the-art sequence models like transformers; generative models (generative adversarial networks and variational autoencoders); and deep reinforcement learning. Coursework will consist of programming assignments in Python (primarily PyTorch). Those registered for 4 credit hours will have to complete a project.

Instructor: Svetlana Lazebnik (slazebni -at- illinois.edu)

Lectures: Wednesdays and Fridays, 3:30PM-4:45PM
Lectures will be delivered live over Zoom and recorded for later asynchronous viewing. Access will be restricted to students logged into the illinois.edu domain. Please check Piazza for links.

TAs: Aiyu Cui (aiyucui2), Adam Stewart (adamjs5), Junting Wang (junting3), Jeffrey Zhang (jz41), Shivani Kamtikar (skk7)

Instructor and TA office hours: See Piazza (and always check for any last-minute announcements of changes)

Contacting the course staff: For emergencies and special circumstances, please email the instructor. For questions about lectures and assignments, use Piazza. For questions about your scores (including regrade requests), email the responsible TAs.

Prerequisites: Multi-variable calculus, linear algebra, data structures (CS 225 or equivalent), CS 361 or STAT 400. No previous exposure to machine learning is required.

Grading scheme:

  Be sure to read the course policies!

Schedule (tentative)

Date Topic Assignments
August 26 Introduction: PPTX, PDF Self-study: Python/numpy tutorial
August 28 Intro to learning and classifiers: PPTX, PDF  
September 2 Linear classifiers: PPTX, PDF  
September 4 Linear classifiers cont. (see slides above)  
September 9 Multi-class classification: PPTX, PDF Assignment 1 out
September 11 Nonlinear classifiers, bias-variance tradeoff: PPTX, PDF  
September 16 Backpropagation: PPTX, PDF  
September 18 Convolutional networks: PPTX, PDF Assignment 1 due September 22
September 23 Convolutional networks cont. (see slides above) Assignment 2 out
September 25 Advanced training: PPTX, PDF
September 30 PyTorch tutorial: Jupyter Notebook
October 2 Object detection: PPTX, PDF Assignment 2 due October 6
October 7 Object detection cont. Assignment 3 out: Part 1, Part 2
October 9 Dense prediction: PPTX, PDF  
October 14 Dense prediction cont. Project proposals due (for 4 credits)
October 16 Self-supervised learning: PPTX, PDF  
October 21 Visualization: PPTX, PDF  
October 23 Adversarial examples: PPTX, PDF  
October 28 Generative adversarial networks  
October 30 Variational autoencoders Assignment 3 due November 3
November 4 Image-to-image translation models Assignment 4 out (tentative)
November 6 Recurrent networks  
November 11 Recurrent networks cont.  
November 13 Sequence-to-sequence models with attention Project progress reports due
November 18 Transformers Assignment 4 due (tentative)
November 20 Deep Q-learning Assignment 5 out (tentative)
December 2 Policy gradient methods  
December 4 Deep RL applications  
December 9 Societal impacts and ethics Assignment 5 due (tentative)


Other deep learning courses with useful materials


Useful textbooks available online

Statement on mental health

Diminished mental health, including significant stress, mood changes, excessive worry, substance/alcohol abuse, or problems with eating and/or sleeping can interfere with optimal academic performance, social development, and emotional wellbeing. The University of Illinois offers a variety of confidential services including individual and group counseling, crisis intervention, psychiatric services, and specialized screenings at no additional cost. If you or someone you know experiences any of the above mental health concerns, it is strongly encouraged to contact or visit any of the University’s resources provided below. Getting help is a smart and courageous thing to do -- for yourself and for those who care about you.

Counseling Center: 217-333-3704, 610 East John Street Champaign, IL 61820

McKinley Health Center:217-333-2700, 1109 South Lincoln Avenue, Urbana, Illinois 61801