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Welcome to Machine Learning in Computer Vision

  1. Please read the FAQ.
  2. Seriously, please read the FAQ.
  3. Here is the Syllabus.
  4. 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.
  5. 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).
  6. Please read the Late Policy.

Time

Lectures: Wed, 14-16 and Thu, 9-11.

Practical session (TIRGUL): Thu, 11-12

Course Staff

Lecturer: 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.

Grading

To 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

Exam Dates

  • Moed Aleph: 10/07/2018
  • Moed Bet: 30/07/2018