Course Overview

This is an advanced undergraduate level / graduate-level course for students who are interested in learning how to apply machine learning algorithms to solve real-world problems. We will start with a quick review of machine learning basics and then focus on a few selected interesting (subjective) topics including communication networks, web search and recommendation, LLMs, generative models, smart grid, and medical applications. We will also discuss some high-impact industry machine learning products and the research problems behind their successes. The class consists of instructor lectures, student-led presentations, class discussions, and class projects.

Prerequisites

Please Note: Instructor approval is needed to register this course. We will check whether the prerequisites are met. These prerequisites are strict. These prerequisites are important for you to be successful in this fast-paced class. Please register for later offerings if you do not meet these prerequisites currently.

For approval, please email the instructor with the EXACT title “COMP597: Registration Approval Request”. In the email body, please list the prerequisite courses you took, and the course grades you got, with each line for one course. Please mark missing prerequisite course(s) in bold and red color. Please also attach (1) your transcript(s) (university and above) and (2) a CV with your detailed project(s) and research or industry/internship experiences. Please include your McGill ID# in the email and your CV. Thanks.

General Information

👨🏼‍🏫 Instructor: Prof. Steve Liu

Email: solve the reCAPTCHA on my webpage (Recommended means for communication. Do NOT use the phone for contact.)

Office: Room 326, McConnell Engineering Building

Office Hours: TBD

Location: Zoom or Office

💁🏼 Teaching Assistant: TBD

Email: TBD

Please note: Emails should be sent from your official McGill email address in order to get the response. Emails not from your official McGill email address will NOT be properly filtered hence will not be responded. Emails should be started with the title “COMPXXX: ***”. Replace XXX with the correct course number. For every email communication, please make sure to use “COMPXXX:” as a single word (with no spaces) as the start of the title and replace *** with your topic/questions, and replace XXX with the correct course number.

Please note: Due to a LARGE number of emails (including spams, unfortunately) I receive every day, emails not started with this title may be categorized as spams by the spam filter and will be missed. We will NOT use WebCT / MyCourses email. Thank you for your understanding.

Academic Integrity: “McGill University values academic integrity. Therefore, all students must understand the meaning and consequences of cheating, plagiarism, and other academic offences under the Code of Student Conduct and Disciplinary Procedures (see

www.mcgill.ca/integrity

⁠

for more information).”

Course Syllabus

Textbooks

Evaluation

Please note: In the event of extraordinary circumstances beyond the University’s control, the evaluation scheme in a Course is subject to change, provided that there be timely communications to the students regarding the change.

Final project evaluation

Late project policy

Click here to see

Schedule

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