|Office:||315 Heller Hall|
|Office Hours:||15:30-16:45 TR, 16:00-17:30 W and by appointment|
|Text:||Mitchell, Machine Learning, McGraw-Hill|
This course will present an introduction to the field of machine learning and the related field of data mining. The course will cover material from the entire textbook (though some of the coverage will be necessarily brief). The textbook will be supplemented with material from research papers on recent developments in machine learning. The course will focus largely on classification learning, though there will also be some coverage of other learning techniques including analytical learning, unsupervised learning and reinforcement learning. The course will include several coding projects in which students will implement learning algorithms.
|Item||Points||Date and Time|
|Midterm Exam 1||125 points||February 22 (Thursday), 14:00-15:15|
|Midterm Exam 2||125 points||April 17 (Tuesday), 14:00-15:15|
|Final Exam||250 points||May 9 (Wednesday), 16:00-17:55|
|Programming Assignments (6)||400 points||TBA|
|Homework Assignments (5)||100 points||TBA|
|Total||1000 points||Grade based on total points|
Copies of the overheads used in class will be made available on the class web page (hopefully before class).
You are responsible for what goes on in class, including lecture material, handouts, and turning in assignments. If you are unable to attend class it is your responsibility to obtain copies of class notes and any materials distributed in class. You may turn in copies of assignments early or have other members of the class turn in an assignment for you.
No exam will be given early. Exams can be made up only in the case of emergencies such as severe illness or death in the immediate family. You must contact me 24 hours in advance in order to arrange a makeup.
All assignments will be collected at the beginning of class on the due date. Late assignments will be penalized 20% of the grade for each working day the assignment is late.
Programming assignments must be your own work. You may discuss general ideas with other students, but should not discuss actual code with others. If you are having problems with an assignment, please come and see me or send me email.
As instructor I shall make every attempt to treat all students equally, without regard to race, religion, color, sex, handicap, age, veteran status, or sexual orientation. I encourage you to talk to me about your concerns of equal opportunity in the classroom. To inquire further about the University's policy on equal opportunity, contact the Office of Equal Opportunity (6827), 255 DAdB.
If you have any disability (either permanent or temporary) that might affect your ability to perform in this class, please inform me at the start of the quarter. I may adapt methods, materials, or testing so that you can participate equitably. To learn about the services that UMD provides to students with disabilities, contact the Access Center (8727), 138 Kirby Plaza, or the Office of Equal Opportunity (8217), 255 DAdB.