Machine Learning (COMP-652 and ECSE-608)
Winter 2017

News

The first class takes place Thursday, Jaunary 5, 2017.


General Information

Where: Trottier, room 0070

When: Tuesday and Thursday, 1:05-2:25pm.

What: The goal of this class is to provide an overview of the state-of-art algorithms used in machine learning. The field of machine learning is concerned with the question of how to construct computer programs that improve automatically with experience. In recent years, many successful applications of machine learning have been developed, ranging from data-mining programs that learn to detect fraudulent credit card transactions, to autonomous vehicles that learn to drive on public highways, and computer vision programs that can recognize thousands of different object types. At the same time, there have been important advances in the theory and algorithms that form the foundation of this field. During this course, we will study both the theoretical properties of machine learning algorithms and their practical applications.


Instructors

Doina Precup
School of Computer Science
Office: McConnell Engineering building, room 111N (left from elevators)
Office Hours: Tuesday and Thursday, 2:30-3:00pm Meetings at other times by appointment only
Phone: (514) 398-6443
E-mail: dprecup@cs.mcgill.ca

Guillaume Rabusseau
School of Computer Science
Office: McConnell Engineering building, room 104N (left from elevators)
Office Hours: TBA. Meetings at other times by appointment only
E-mail: guillaume.rabusseau@mail.mcgill.ca


Teaching assistants

Tianyu Li, office hours TBA

Additional TA TBA


References

There is no required textbook. However, there are several good machine learning textbooks describing parts of the material that we will cover. The schedule will include recommended reading, either from these books, or from research papers, as appropriate. Lecture notes and other relevant materials are linked to the lectures web page. Assignments are linked to the assignments web page

MyCourses will be used only for bulletin board, discussion groups and assignment submission and grading.