The Course Covers Practical and Theoretical Aspects of Deep Learning With Emphasis On Computer Vision and Language Processing. The Course Will Cover Shallow Networks, Deep Networks Convolutional Networks and Their Theoretical Analysis. Learning Outcomes#at The End of The Course The Student Will Know# 1. to Execute Various Deep Learning Architectures. 2. to Analyze Their Generalization Properties

Faculty: Data and Decision Sciences
|Undergraduate Studies |Graduate Studies
Pre-required courses

46211 - Deep Learning or 97209 - Machine Learning 2 or 236781 - Deep Learning On Computation

Semestrial Information

Weekly Hours

3.5 Academic Credit • 2 Lecture Hours • 2 Discussion Hours • 3 Project Hours

Responsible(s)

Itai Gat


Exams
Session A: 17-02-2023 Session B: 13-03-2023
Registration Groups
11
Lecture Thursday 11:30 - 13:30 נהול 216 | Tamir Hazan
Exercise Monday 08:30 - 10:30 בלומפילד 151 | Itai Gat
Weekly Hours

3.5 Academic Credit • 2 Lecture Hours • 2 Discussion Hours • 3 Project Hours

Responsible(s)

Igor Drozdov


Exams
Session A: 21-07-2022 09:00 - 12:00
  • נהול 112. 214. 215. 216.
  • בלומפילד 526.
Session B: 21-10-2022 09:00 - 12:00
  • נהול 112. 215. 216.
  • בלומפילד 526.

Registration Groups
11
Lecture Tuesday 10:30 - 12:30 נהול 112 | Tamir Hazan
Exercise Wednesday 08:30 - 10:30 בלומפילד 151 | Igor Drozdov
12
Lecture Tuesday 10:30 - 12:30 נהול 112 | Tamir Hazan
Exercise Tuesday 12:30 - 14:30 נהול 216 | Igor Drozdov
13
Lecture Tuesday 10:30 - 12:30 נהול 112 | Tamir Hazan
Exercise Wednesday 10:30 - 12:30 נהול 214 | Naama Berman
Weekly Hours

3.5 Academic Credit • 2 Lecture Hours • 2 Discussion Hours • 3 Project Hours

Responsible(s)

Tamir Hazan


Exams
Session A: 18-02-2021 13:00 - 16:00 Session B: 14-03-2021 13:00 - 16:00
Registration Groups
11
Lecture Monday 14:30 - 16:30 נהול 216 | Tamir Hazan
Exercise Monday 16:30 - 18:30 נהול 216 | Guy Lorberbom
12
Lecture Monday 14:30 - 16:30 נהול 216 | Tamir Hazan
Exercise Tuesday 10:30 - 12:30 בלומפילד 527 | Itai Gat