applied machine learningLecturer: Prof. Moshe Sipper
|
למידת מכונה יישומית |
202.2.6511, 4 credits
בסמסטר ב', תשפ"ד הקורס מקוון
🎓 Prerequisites: Algorithms, Linear algebra, Probability
💻 Not a prerequisite but (really) good to know: Python
✍ Contents and lesson plan
🗣 Attendance is not mandatory: online/offline Zoom is okay
💯 Grade:
💻 Not a prerequisite but (really) good to know: Python
✍ Contents and lesson plan
🗣 Attendance is not mandatory: online/offline Zoom is okay
💯 Grade:
- Final exam (70%) and 3 coding assignments (each 10%)
- Exam: multiple choice
- Assignments: teams of 2 or 3
- To pass the course you must:
- (1) Take and pass the test.
- (2) Submit and pass all homework assignments.
- Final grade = 0.7*exam + 0.1*a₁ + 0.1*a₂ + 0.1*a₃ (aᵢ is assignment i)