EECS 545: Machine Learning.

University of Michigan, Fall 2009

Instructor: Clayton Scott
Classroom: 1690 CSE
Time: MW 10:30-12
Office: 4433 EECS
Office hours: Monday 2-4 PM

GSI: Gowtham Bellala
Uniqname: gowtham
Office hours: TBA.

Final Projects from Fall 2009

Final Projects from Fall 2007

Required text: None.

Recommended texts:

Additional references

Machine learning bibliography

Prerequisites: (the current formal prerequisite is currently listed as EECS 492, Artificial Intelligence, but this is inaccurate)

Students with most but not all of this background may be able to catch up during the semester.

Lecture notes:

Supervised Learning Unupervised Learning Reinforcement Learning Additional Topics

Homework: 35%
Exam: 10%, Thursday Nov. 12, 6-9 PM, location TBA
Participation and attendance: 5%
Final project: 50%

Homework will be assigned every one or two weeks. The assignments will be much smaller and easier toward the end of the course, when you are working on your project.

Computer programming
Most or all assignments will involve some computer programming. MATLAB will serve as the official programming language of the course. You are free to use another language, such as R, but I will sometimes provide you with fragments of code, or suggested commands, in MATLAB.

Group work:
Group work will take place on two levels. You will work on homeworks in small groups of 2, and the final project in large groups of 3 or 4. I will help you find groups as needed.

Exam: Time and location TBD.
Collaboration of any form will not be allowed. Allowed materials will be specified in advance of the exam.

Final Project:
There will be a final, open-ended group project. The project must explore a methodology or application (and preferably both) not covered in the lectures. The work must not simply reproduce the results of a paper, but explore some new aspect of a problem. I will assist groups in selecting a topic as much as necessary. The project will be judged based on clarity, thoroughness, and originality. The project will be graded based on the following components:

All written documents must be single spaced, 12 point font, with at least one inch margins. Page limits include everything, such as figures, tables, and references. Figure captions should be self-contained.

Each group will turn in one product representative of the group. Solutions to homework problems from outside sources may not be used.

Honor Code
All undergraduate and graduate students are expected to abide by the College of Engineering Honor Code as stated in the Student Handbook and the Honor Code Pamphlet.

Students with Disabilities
Any student with a documented disability needing academic adjustments or accommodations is requested to speak with me during the first two weeks of class. All discussions will remain confidential.