Akademik Dersler - Tanıtım


Code - Course Title	BİM488 - Introduction to Pattern Recognition
Course Type	Area Elective Courses
Language of Instruction	İngilizce
Laboratory + Practice	3+0
ECTS	4.5
Course Instructor(s)	PROFESÖR DOKTOR SERKAN GÜNAL
Mode of Delivery	Face to face
Prerequisites	Not available
Courses Recomended	Statistics, Linear Algebra.
Required or Recommended Resources	- A. Géron. Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems. O'Reilly Media, Inc., 2022.- S. Theodoridis and K. Koutroumbas. Pattern Recognition (4th Ed.), Academic Press, 2009.- C. M. Bishop and N. M. Nasrabadi. Pattern Recognition and Machine Learning, Springer, 2006.
Recommended Reading List	- A. Géron. Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems. O'Reilly Media, Inc., 2022.- S. Theodoridis and K. Koutroumbas. Pattern Recognition (4th Ed.), Academic Press, 2009.- C. M. Bishop and N. M. Nasrabadi. Pattern Recognition and Machine Learning, Springer, 2006.
Assessment methods and criteria	Midterm Exam, Homework, Final Exam.
Work Placement	Not available
Sustainability Development Goals	Quality Education , Industry, Innovation and Infrastructure

Weeks	Topics
Week - 1	Introduction
Week - 2	Review of Probability
Week - 3	Review of Linear Algebra
Week - 4	Introduction to Matlab
Week - 5	Classification Algorithms - Part I
Week - 6	Classification Algorithms - Part II
Week - 7	Classification Algorithms - Part III
Week - 8	Feature Selection
Week - 9	Text Classification
Week - 10	Speech Recognition
Week - 11	Face Recognition
Week - 12	Pattern Recognition with Deep Learning
Week - 13	Course Recap
Week - 14	Project Presentations

Assessment Method and Passing Requirements
	Quamtity	Percentage (%)
1.Midterm Exam	1	30
Homework	1	20
Final Exam	1	50
Toplam (%)		100