CENG501 DEEP LEARNING
| Course Code: | 5710501 |
| METU Credit (Theoretical-Laboratory hours/week): | 3 (3.00 - 0.00) |
| ECTS Credit: | 8.0 |
| Department: | Computer Engineering |
| Language of Instruction: | English |
| Level of Study: | Graduate |
| Course Coordinator: | Assoc.Prof.Dr. EMRE AKBAŞ |
| Offered Semester: | Fall and Spring Semesters. |
Course Objectives
At the end of the course, the students will be expected to:
- Learn various deep neural network based representation models and learning methods,
- Apply such deep learning models/methods to various learning problems.
- Learn about deep hierarchies in human brain,
Course Content
For course details, see https://catalog2.metu.edu.tr.Course Learning Outcomes
Students who passed the course will be able:
- to understand the theory behind deep learning methods such as Convolutional Neural Networks, Autoencoders and Boltzmann Machines,
- to develop their own framework for implementing these deep learning methods,
- to have a grasp of the trends in deep learning research,
- to have a feeling of when to use or avoid deep learning methods.