Subject: Subject Sylbus: Deep Learning - 097200

Deep Learning - 097200
Credit
Points
3.5
 
Given In
Semester
a
 
  Lecture Exercise Laboratory Project or
Seminar
House
Work
Weekly
Hours
2 2   3 3

Determination of the grade according to progress during the semester and the submission of the final thesis


Prerequisites: ( Data Structures 1 234218
and Introduction to Machine Learning 236756 )
or ( Data Structures and Algorithms 094224
and Machine Learning 1 096411 )
or ( Int. to Data Structur and Algorithms 044268
and Machine Learning 046195 )
 
Overlapping Courses: Deep Learning and Its Applications 236777


The Course Covers Practical and Theoretical Aspects of Deep 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




System of hours to the semesters
Semester Previous Semester information 01/2020 2020/2021 Winter Semester

Created in 08/03/2021 Time 15:07:03