Course Announcements
Updated Information
- [Apr. 2] Course webpage is setup ready.
- [Aug. 2] Course Piazza page is setup ready.
- [Aug. 2] Course collab page is setup ready.
- [Aug. 23] Course schedule page is setup ready.
- [Aug. 26] Q0 is out. Please evaluate yourself. This quiz is the minimum math requirements for the course.
- [Aug. 29] HW1 is out. due in about 10 days.
Course Information
General Description
- Machine Learning is concerned with computer programs that automatically improve their performance through experience. This 3-credit course covers introductory topics about the theory and practical algorithms for machine learning from a variety of perspectives. Topics include supervised learning, unsupervised learning and learning theory.
- Assignments include multiple short programming and writing assignments for hands-on experiments of various learning algorithms, multiple in-class quizzes, an in-class mid-term and an in-class final exam.
Prerequisite:
- Required courses as prerequisite: Calculus, Basic linear algebra, Basic Probability and Basic Algorithm. Statistics is recommended. Students should already have good programming skills and can program with python (required ! ).
Instructor
- Prof. Yanjun (Jane) Qi, Office hour: Mon 8am-9am @ Rice Hall 503
- Teaching Assistant: Jack Lanchantin / Office hour: 5:30pm-6:30pm Wed @ Rice 504
- Teaching Assistant: Muthuraman Chidambaram / Office hour: 5:30pm-6:30pm Wed @ Rice 504
- Teaching Assistant: Weilin Xu / Office hour: 5:30pm-6:30pm Mon @ Rice 504
- Teaching Assistant: Kamran Kowsari / Office hour: 5:30pm-6:30pm Mon @ Rice 504
Course Websites
- Course Collab page to submit assignments and project reports.
- Course schedule and materials are listed @
http://www.cs.virginia.edu/yanjun/teach/2016f/.
- Course Piazza page for QA of exams, quizzs, class-discussions, assignments and project reports.
Text Book
- No required text book.
- Course slides and handouts are self-contained.
Course Grading Policy
The grade will be calculated as follows:
- Assignments (60%, with six assignments)
- Midterm (20%)
- Final (20%)
-
Quizzes (5%)
Additional Non-Linear Constraint
- In order to pass the course, the average of your midterm and final
must also be "pass".
Assignment due dates, Lateness
and Extensions
- Unless otherwise specified, assignments should be submitted through collab and are due
at 11:59pm on the due date .
- Programming solutions should be placed in each student's appropriate
Collab directory.
-
Multiple in-class quizzes will be given over the whole semester. Please do not miss classes in order to take these pop quizzes.
- Each student has three extension days to be used at his or
her own discretion throughout the entire course. Your grades would be
discounted by 15% per day when you use these 3 late days.
You could use the 3 days in whatever combination you like. For example,
all 3 days on 1 assignment (for a maximum grade of 55%) or 1 each day
over 3 assignments (for a maximum grade of 85% on each).
After you've used all 3 days, you cannot get credit
for anything turned in late.
Logistics Information
- Announcements are being emailed to the course mailing list.
- A welcome note will be sent to the mailing list early in the semester.
- If you do not receive the welcome message by Sept. 5, 2016, please
send mail to the instructor.
- Errata and answers to questions are being discussed and answered
on the course piazza size and through emailist.
The Course Schedule Reference : The official Academic Calendar at
UVA Registrar.
Useful Links :