MMI702 MACHINE LEARNING FOR MULTIMEDIA INFORMATICS
| Course Code: |
9090702 |
| METU Credit (Theoretical-Laboratory hours/week): |
3(3-0) |
| ECTS Credit: |
8.0 |
| Department: |
Multimedia Informatics |
| Language of Instruction: |
English |
| Level of Study: |
Graduate |
| Course Coordinator: |
|
| Offered Semester: |
Fall Semesters. |
Course Content
The main objective of this course is to provide a theoretical and practical coverage of machine learning in multimedia domain. The main topics to be covered during the course are supervised learning, Bayesian Decision Theory, parametric methods, multivariate methods, dimensionality reduction, clustering, decision trees and Hidden Markov Models. The course will not only focus on providing a theoretical background to the students, but will also encourage them to implement the algorithms learned in the class and to analyze practical examples. The students will be given a term project and various assignments to implement the algorithms taught during the course. Also, reading assignments focusing on the recent research on Machine Learning will be given and discussed during the lectures.
