GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION

PATTERN RECOGNITION/5191329

Course Title:	PATTERN RECOGNITION
Credits	3	ECTS	7.5
Semester	1	Compulsory/Elective	Elective

COURSE INFO

-- LANGUAGE OF INSTRUCTION

Turkish

-- NAME OF LECTURER(S)

Assoc.Prof.Dr. Hasan Şakir BİLGE

-- WEB SITE(S) OF LECTURER(S)

w3.gazi.edu.tr/~bilge

-- EMAIL(S) OF LECTURER(S)

bilge@gazi.edu.tr

-- LEARNING OUTCOMES OF THE COURSE UNIT

Applying of classification methods in a sample problem successfully
Obtaining the ability of effective use of feature selection and dimensionality reduction
Understanding that pattern recognition can be applied to different problems in a similar way.

-- MODE OF DELIVERY

The mode of delivery of this course is Face to face

-- PREREQUISITES AND CO-REQUISITES

There is no prerequisite or co-requisite for this course

-- RECOMMENDED OPTIONAL PROGRAMME COMPONENTS

There is no recommended optional programme component for this course

--COURSE CONTENT
1. Week	General introduction
2. Week	Classifiers based on Bayes decision theory
3. Week	Linear classifiers
4. Week	Linear discriminant functions
5. Week	Non linear classifiers
6. Week	Support vector machines
7. Week	Support vector machines
8. Week	Feature extraction
9. Week	Feature extraction
10. Week	Linear transformations
11. Week	Feature selection
12. Week	Feature selection
13. Week	Dimensionality reduction
14. Week	Clustering
15. Week	Clustering
16. Week	Project presentations

-- RECOMMENDED OR REQUIRED READING

1. Pattern Recognition, S. Theodoridis, K. Koutroumbas, Academic Press, 2008. 2. Pattern Classification, R.O. Duda, P.E. Hart, D.G. Stork, Wiley, 2000.

-- PLANNED LEARNING ACTIVITIES AND TEACHING METHODS

Lecture, Question & Answer, Practise

-- WORK PLACEMENT(S)

-- ASSESSMENT METHODS AND CRITERIA

	Quantity	Percentage
Mid-terms	0	0
Assignment	1	30
Exercises	1	30
Projects	1	30
Practice	0	10
Quiz	0	0
Contribution of In-term Studies to Overall Grade		60
Contribution of Final Examination to Overall Grade		40

-- WORKLOAD

Efficiency	Total Week Count	Weekly Duration (in hour)	Total Workload in Semester
Theoretical Study Hours of Course Per Week	3	14	42
Practising Hours of Course Per Week			0
Reading	1	14	14
Searching in Internet and Library	1	14	14
Designing and Applying Materials	1	14	14
Preparing Reports	1	14	14
Preparing Presentation	1	14	14
Presentation	2	25	50
Mid-Term and Studying for Mid-Term			0
Final and Studying for Final	1	30	30
Other			0
TOTAL WORKLOAD:			192
TOTAL WORKLOAD / 25:			7.68
ECTS:			7.5

-- COURSE'S CONTRIBUTION TO PROGRAM

NO	PROGRAM LEARNING OUTCOMES	1	2	3	4	5
1	Can improve his computer engineering knowledge					X
2	Can acknowledge the multidiciplinary aspects of computer engineering					X
3	Can use his computer engineering knowledge					X
4	Can acknowledge the multidiciplinary aspects of computer engineering					X
5	Can use his computer engineering knowledge to solve problems					X
6	Can define computer engineering problems					X
7	Can propose solutions to computer engineering problems					X
8	Can solve computer engineering problems					X
9	Can evaluate solutions using qualtiy metrics					X
10	Can come up with new approaches to application problems					X

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GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR