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. 3] Course schedule page is setup ready.
• [Aug. 26] Q0 is out. Please evaluate yourself. This quiz is the minimum math requirements for the course.
• [Sept. 3] HW1 is out. due in two weeks.

General Description

• This is a graduate-level machine learning course.
• 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 a student project, multiple short programming and writing assignments for hands-on experiments of various learning algorithms, multiple in-class quizzes, and an in-class mid-term 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, (yanjun@virginia.edu), Office hour: Thur 5pm-6pm @ Rice 503
  
• Teaching Assistant: Ritambhara Singh (rs3zz@virginia.edu), Office hour: 6pm-7pm Wed @ Rice 504
• Teaching Assistant: Beilun Wang (bw4mw@Virginia.EDU), Office hour: Wed 5pm-6pm @ 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/2015f/.
• 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 mostly self-contained.

Course Grading Policy

The grade will be calculated as follows:

• Assignments (50%, with each assignment 10%)
• Midterm (25%)
• Final project (25%)

• In order to pass the course, the average of your midterm and final must also be "pass".

• Unless otherwise specified, assignments should be submitted through collab and are due at 11:59pm on the due date .
• 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