CNG501 DEEP LEARNING
Course Code: | 3550501 |
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: | |
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.