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SECOND CYCLE - MASTER'S DEGREE
THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES
COMPUTER ENGINEERING DEPARTMENT
1281 Computer Engineering
Course Information
Course Learning Outcomes
Course's Contribution To Program
ECTS Workload
Course Details
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COURSE INFORMATION
Course Code
Course Title
L+P Hour
Semester
ECTS
CENG 525
PATTERN RECOGNITION
3 + 0
2nd Semester
7,5
COURSE DESCRIPTION
Course Level
Master's Degree
Course Type
Elective
Course Objective
The main objective of this course is teaching students the pattern recognition methods.
Course Content
Introduction to pattern recognition, discrete events and Bayes rule, expected loss, Bayes risk, Gaussian decision functions, error bounds, noisy features, ML parameter estimation, principal component analysis (PCA), eigen faces, non parametric estimation, k-NN prediction, linear discriminant analysis
Prerequisites
No the prerequisite of lesson.
Corequisite
No the corequisite of lesson.
Mode of Delivery
Face to Face
COURSE LEARNING OUTCOMES
1
Select the most appropriate method for applying to a given object or data
2
Analyze the pattern recognition methods and the results
3
Comprehend the effects of noise on the data that is obtained from real-life and extract patterns from these noisy data
COURSE'S CONTRIBUTION TO PROGRAM
Data not found.
ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
Activities
Quantity
Duration (Hour)
Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)
14
3
42
Hours for off-the-classroom study (Pre-study, practice)
14
5
70
Assignments
5
8
40
Mid-terms
1
15
15
Final examination
1
28
28
Total Work Load
ECTS Credit of the Course
195
7,5
COURSE DETAILS
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L+P:
Lecture and Practice
PQ:
Program Learning Outcomes
LO:
Course Learning Outcomes
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Home Page
About University
Name And Address
Acedemic Authorities
General Discription
Academic Calendar
General Admission Requirements
Recognition of Prior Learning
General Registration Procedures
ECTS Credit Allocation
Academic Guidance
Information For Students
Cost Of Living
Accommodation
Meals
Medical Facilities
Facilities for Special Needs Students
Insurance
Financial Support for Students
Student Affairs
Learning Facilities
International Programs
Language Courses
Internships
Sports Facilities and Leisure Activities
Student Associations
Practical Information for Mobile Students
Degree Programmes