George
Mason University
The Volgenau School of Engineering
Department of Computer Science
CS 782 Machine Learning
Meeting time: Wednesday 4:30 pm – 7:10 pm
Meeting location: Nguyen Engineering Building 1103
Instructor: Dr. Gheorghe Tecuci, Professor of Computer Science
Office hours: Wednesday
7:20 pm – 8:20 pm
Office: Nguyen Engineering Building 4613
Phone: 703 993 1722
E-mail: tecuci at gmu dot edu
Course Description
Machine Learning is concerned with the development of computer
systems that are able to improve their performance at some task by learning
from input data, from their own problem solving experience, and/or from a user.
This course presents the principles, strategies, major methods, systems, applications,
open issues, and research directions in Machine Learning. Covered topics
include: Inductive learning, Decision trees learning, Rule induction (Learning
rule sets, Inductive logic programming), Instance-based approaches (k-NN,
Case-based, Analogy), Bayesian learning (Naïve Bayes, Bayesian network, EM), Regression
(Linear, Locally weighted) Neural networks and deep learning, Model ensembles (Bagging,
Boosting, ECOC, Staking), Support vector machines, Abductive learning, Learning
assistants, and Learning theory. The course will include experimentation with
learning systems implementing the methods discussed in class. It will also
include a project involving significant outside study and preparation of a
presentation and demo to the class.
Detailed lecture notes with required and recommended readings will be posted before each class meeting.
This course will use Blackboard (see http://gmu.blackboard.com) to post lecture notes, papers, assignments, and grades. The students will also submit their assignments through Blackboard. Students have accounts on Blackboard and can download the posted documents by going to courses.gmu.edu and logging in using their Mason ID and passwords.
Grading Policy
The course grade will be computed as follows:
Assignments and class participation: 10%
Project: 24%
Midterm exam: 33%
Final exam 33%
Exam Dates
Mid-term exam: Wednesday 18 March at 4:30PM
Final exam: Wednesday 6 May at 4:30PM
Email Communication
Email to tecuci@gmu.edu and start the subject of the message with CS782.
Please try to limit
the size of the files you are emailing.
GMU Email Accounts
Students must activate their GMU email accounts to receive important University information, including messages related to this class.
Office of Disability Services
If you are a student with a disability and you need academic accommodations, please see me and contact the Office of Disability Services (ODS) at (703) 993-2474. All academic accommodations must be arranged through the ODS. http://ods.gmu.edu.
Other Useful Campus Resources
Writing Center: A114 Robinson Hall; 703 993 1200; http://writingcenter.gmu.edu
University Libraries “Ask a Librarian” http://library.gmu.edu/mudge/IM/IMRef.html
Counseling And Psychological Services (CAPS): 703 993 2380; http://caps.gmu.edu
University Policies
The University Catalog, http://catalog.gmu.edu, is the central resource for university policies affecting student, faculty, and staff conduct in university affairs.
Honor Code
You are expected to abide by the GMU honor code.
Information on the university honor code can be found at http://academicintegrity.gmu.edu/honorcode/.
Additional departmental CS information: http://cs.gmu.edu/wiki/pmwiki.php/HonorCode/CSHonorCodePolicies