CSCI 680-1: Machine Learning

Fall 2019

Meeting place: McGlothlin-Street Hall 002
Meetings: 11:00-12:20 (Tu. and Th.)
Instructor: Qun Li (liqun@cs)
Office: McGlothlin-Street 118

Office Hours:
2-5PM Tuesday

Course Description:

This course provides an introduction to machine learning and statistical pattern recognition. Possible topics include both supervised and unsupervised learning as well as learning theory, reinforcement learning and control. The course gives students the ideas and intuition behind modern machine learning methods.

Prerequisites:

Familiarity with basic probability theory, linear algebra, and calculus.

Textbook:

No required textbook.

Quizzes:

Quizzes will be given to students.

Projects:

Each student will conduct a project (ideally two people in a group) over the course of the semester.

Exams:

Time will be scheduled for in-class midterm and final exams.

Important Dates:

Add/Drop (9/6/2019), Withdraw (10/28), Final Exam (12/10 2-5PM)

Grades:

Your grade in the course will be assigned using the following weights (tentatively):
20% Quizzes
30% Midterm exam
30% Final exam
20% Project

Schedule:

Week 1-4: Supervised learning
Week 5-9: Unsupervised learning
Week 10-12: Reinforcement learning
Week 13-15: Deep learning

Honor code:
Honor code applies to this class. Students are encouraged to work together to do homework problems. What is important is a student's eventual understanding of homework problems, and not how that is achieved. Students may consult any source, except for another student's final draft, in learning how to do homework problems. Students must state what sources they have consulted, with whom they have collaborated, and from whom they have received help.

Student Accessibility Services:
William & Mary accommodates students with disabilities in accordance with federal laws and university policy. Any student who feels they may need an accommodation based on the impact of a learning, psychiatric, physical, or chronic health diagnosis should contact Student Accessibility Services staff at 757-221-2512 or at sas@wm.edu to determine if accommodations are warranted and to obtain an official letter of accommodation. For more information, please see www.wm.edu/sas.