University of Toronto
Computer Science
Winter 2025
All course information (except place/time) is subject to change until January 8, 2025. After that point, any significant changes will be announced to the class mailing list.
Machine learning is a powerful set of techniques that allow computers to learn from data rather than having a human expert program behaviour by hand. Neural networks are a class of machine learning algorithms originally inspired by the brain but have recently seen much success in practical applications. They're at the heart of production systems at companies like Google and Meta for face recognition, speech-to-text, and language understanding.
This course gives an overview of foundational ideas and the recent advances in neural net algorithms. Roughly the first 2/3 of the course focuses on supervised learning --- training the network to produce a specified behaviour when one has many labelled examples of that behaviour. The last 1/3 focuses on unsupervised learning and reinforcement learning.
| Section | Instructor | Lecture Time | Lecture Room | Tutorial Time | Tutorial Room |
|---|---|---|---|---|---|
| LEC 101/2001 | Alice Gao | Tue 3-5pm | SS 1083 | Thu 3-4pm | MP 137 |
| LEC 201/2101 | Roger Grosse | Wed 9-11am | WI 1016 | Fri 10-11am | WI 1016 |
| LEC 301/2201 | Nikita Dhawan | Wed 1-3pm | ES B149 | Fri 1-2pm | ES B149 |
Instructor: Alice Gao
Hi! I'm Professor Alice Gao (she/her/hers), one of your instructors for this course. Feel free to call me Professor, Professor Gao, or Alice. I'm an assistant professor in the computer science department, and this is my third year at UofT. I've taught Intro to AI (CSC384) and Intro to ML (CSC311) regularly. This is my first time teaching Deep Learning (CSC413), and I'm very excited! If you enjoy this course, consider taking another one with me. I'd love to get to know you better! I also work on research projects in computer science education. If you're interested in research, consider taking CSC494/495 with me. We'll work on a research project and learn together! For more information on my teaching experience, research projects, and how to request a reference letter, visit my website.
Please do not email me regarding this course. Instead, attend my office hours or send a message to the course email account (see the "Seeking Help" section below for details). My office is in Bahen 4240. If you want to chat, I recommend making an appointment beforehand.
Office Location: Bahen 4240
E-mail address: [email protected]
Instructor: Roger Grosse
E-mail Address: [email protected]
Hi! I’m Roger Grosse (he/him/his), another instructor for the course. You can call me Roger. I’m as Associate Professor of Computer Science, focused on deep learning and AI alignment. I last taught this course in 2019, and am looking forward to getting back into it! For more information, please check out my website.
Office location: Pratt 290F (that’s the D. L. Pratt building, not the E. J. Pratt Library!)
Email: [email protected]
Instructor: Nikita Dhawan
Hello! My name is Nikita (she/her/hers), and I’ll teach one of the sections of this course. I am 4th-year PhD student at UofT. My research focuses on machine learning and building or using neural nets, which means it uses or has used a lot of the techniques in this course! Please feel free to come chat about topics in the course, research at the intersection of ML and healthcare, or anything else, during my office hours. More information can be found on my website.
Office Location: Bahen 2272 (for office hours only)
E-mail Address: [email protected]
Lecture recordings will be generated and posted automatically on the OCCS Student App. Remember that course videos and materials belong to your instructor and the University and are protected by copyright. You are permitted to download videos and materials for your own academic use, but you may not copy, share, or otherwise distribute them without explicit permission from the instructor.