Welcome,
Guest
.
Login
.
Türkçe
NİNOVA
COURSES
HELP
ABOUT
Where Am I:
Ninova
/
Courses
/
Institute of Science and Technology
/
BLG 561E
/
Course Informations
Return to Faculty
Home Page
Course Information
Course Weekly Lecture Plan
Course Evaluation Criteria
Course Information
Course Name
Turkish
Derin Öğrenme
English
Deep Learning
Course Code
BLG 561E
Credit
Lecture
(hour/week)
Recitation
(hour/week)
Laboratory
(hour/week)
Semester
1
3
3
-
-
Course Language
English
Course Coordinator
Gözde Ünal
Course Objectives
To introduce main techniques in Deep Learning
2. To understand the mathematical principles of optimization and regularization of deep learning methods
3. To be able to design deep neural networks for various problems in artificial intelligence
4. To implement solutions to learning problems using various deep neural network techniques
Course Description
In this course, the following topics are covered in the area of deep learning: Neural Networks and Convolutional Neural Networks, Optimization and Regularization, Supervised and Unsupervised Methods, Discriminative Networks, Training of Networks, Deep Generative Networks, Adversarial methods, Classification applications, Recurrent Neural Networks, Temporal Prediction applications, Advanced deep learning techniques and applications such as Deep Reinforcement Learning.
Course Outcomes
Pre-requisite(s)
Required Facilities
Other
Textbook
Other References
Courses
.
Help
.
About
Ninova is an ITU Office of Information Technologies Product. © 2024