We emphasize again that the course has prerequisites which we fully enforce this semester.
The prerequisites are *both*:
(1) A course in probability (094412, 104034, or equivalent).
(2) A course in numerical algorithms (234125, 104283, 095295, 084135, or 034033).
(*) As an alternative to numerical algorithms we allow a course in optimization (236330, 046197, or 104193).
Students who registered to our course without these prerequisites, are asked to cancel their registration ASAP.
Please be considerate of other students who wish to register.
|עדכון אחרון ב- 13/1/2021, 13:33:39 Last updated on 13/1/2021, 13:33:39 Последняя модификация 13/1/2021, 13:33:39 تمت الحتلنة الأخيرة ب- 13/1/2021, 13:33:39|
Initial course announcements
The machine learning course (236756) of the CS faculty is being updated.
Previously, the course was given in two different "versions": winter (more theoretical) and spring (more practical).
Looking forward, we aim to unify the course and create a blend of theory and practice.
We started this change during the last semester (Winter 20/21), and will continue it during the upcoming spring semester.
The course should give a clear and sound mathematical understanding of machine learning.
The students will also employ the learned machine learning algorithms to solve practical problems, mainly through the assignments.
To create a common mathematical language, the following prerequisites will be enforced in the coming spring semester:
1. Probability (094412 or 104034).
2. Numerical algorithms (234125, 104283, 095295, 084135, or 034033) or Optimization (236330, 046197, or 104193).
We will make effort to publish the course's syllabus and exact policy during the next week.
The course staff
|פורסם ב- 6/1/2021, 21:41:25 Created on 6/1/2021, 21:41:25 Создано 6/1/2021, 21:41:25 تم النشر ب- 6/1/2021, 21:41:25|