Course Identification

Title:

Basic Readings in Deep Learning

Code:

20184232

Lecturers and Teaching Assistants

Lecturers:

Prof. Ronen Basri

TA's:

N/A

Course Schedule and Location

Year:

2018

Semester:

Second Semester

When / Where:

Tuesday, 16:15 - 18:00, Jacob Ziskind Building, Rm 155

First Lecture:

20/03/2018

Field of Study, Course Type and Credit Points

Mathematics and Computer Science: Elective; 2.00 points

Comments

Course is intended for first year students. Priority will be given to students from the Math and CS faculty. Attendance is mandatory. Course requirements: at each class one student should lecture on a chapter from the course book, or other assigned reading material. All participants should read the presented chapter before class.

Prerequisites

No

Restrictions

Participants:

15

Language of Instruction

English

Attendance and participation

Obligatory

Grade Type

Pass / Fail

Grade Breakdown (in %)

Attendance

50%

Seminar:

50%

Evaluation Type

Seminar

Scheduled date 1

Date / due date

N/A

Location

N/A

Time

-

Remarks

N/A

Estimated Weekly Independent Workload (in hours)

2

Syllabus

The course will cover basic concepts in deep learning by going through parts 2 and 3 of "Deep Learning" by Ian Goodfellow and Yoshua Bengio and Aaron Courville. Supplementary reading can be found in "Neural Networks and Deep Learning" by Michael Nielsen.

Learning Outcomes

Become familiar with basic concepts in deep learning.

Reading List

1. "Deep Learning" by Ian Goodfellow and Yoshua Bengio and Aaron Courville.

2. "Neural Networks and Deep Learning" by Michael Nielsen.

Website

N/A