Course Identification

Title:

Topics in deep neural networks

Code:

20184023

Lecturers and Teaching Assistants

Lecturers:

Prof. Eran Segal

TA's:

N/A

Course Schedule and Location

Year:

2018

Semester:

Full Year

When / Where:

Tuesday, 11:15 - 12:00, Goldsmith, Rm 208

First Lecture:

31/10/2017

Field of Study, Course Type and Credit Points

Mathematics and Computer Science: 2.00 points

Comments

N/A

Prerequisites

No

Restrictions

Participants:

30

Language of Instruction

English

Attendance and participation

Required in at least 80% of the lectures

Grade Type

Pass / Fail

Grade Breakdown (in %)

Attendance

20%

Seminar:

80%

Evaluation Type

Seminar

Scheduled date 1

Date / due date

N/A

Location

N/A

Time

-

Remarks

N/A

Estimated Weekly Independent Workload (in hours)

3

Syllabus

Advanced topics in Deep Neural Networks, including network architectures, network optimization procedures, adversarial networks, reinforcement learning, generlization

Learning Outcomes

Upon successful completion of the course students will be able to:

1. Gain a theoretical and practical understanding of neural network algorithms and optimization procedures, as well as applications to real life datasets

Reading List

N/A

Website

N/A