Welcome to Machine Learning in Computer Vision
- Please read the FAQ.
- Seriously, please read the FAQ.
- Here is the Syllabus.
- This is a self-contained class in the sense that background in neither computer vision nor machine learning will be assumed; particularly, introductory classes in these topics are not prerequisites.
- This class is recommended for both undergrads and grad students interested in computer vision and machine learning. This CS class is also open to students from Electrical Engineering, Math, Physics, and Cog-Sci, provided they have taken suitable equivalents to the class’ prerequisites (and provided that there are enough open spaces in the class).
- Please read the Late Policy.
TimeLectures: Wed, 14-16 and Thu, 9-11.
Practical session (TIRGUL): Thu, 11-12
Course StaffLecturer: Oren Freifeld. Office Hour: Wed, 16:15-18:15 at Room 204, Bld 37
Teaching Assistant: Ron Shapira Weber. Office Hour: Thu, 12:00-13:00 at Room 302, Bld 37.
GradingTo pass the class, you must pass the exam. Assuming a passing grade in the exam, the final grade will consist of:
- 50% = exam grade
- 50% = homework grade
- Moed Aleph: 10/07/2018
- Moed Bet: 30/07/2018