Akademik Dersler - Tanıtım


Code - Course Title	BİM453 - Introduction to Machine Learning
Course Type	Area Elective Courses
Language of Instruction	İngilizce
Laboratory + Practice	3+0
ECTS	4.5
Course Instructor(s)	DOÇENT MEHMET KOÇ
Mode of Delivery	The mode of delivery of this course is Face to face.
Prerequisites	There is no prerequisite or co-requisite for this course.
Courses Recomended	Linear Algebra.
Recommended Reading List	S. Theodoridis and K. Koutroumbas, Pattern Recognition (4th Edition), Academic Press, 2009.
Assessment methods and criteria	2 Midterm Exams, 1 Final Exam, Assignments, Project.
Work Placement	None.
Sustainability Development Goals

Weeks	Topics
Week - 1	Introduction to Learning Algorithms
Week - 2	Linear Algebra
Week - 3	Linear Regression with One Variable
Week - 4	Linear Regression with Multiple Variables
Week - 5	Supervised Learning Algorithms and Classification
Week - 6	Regression and Classification with Neural Networks Models
Week - 7	Decision Tree Learning
Week - 8	Naive Bayes Classifier and Bayesian Networks
Week - 9	Genetic Algorithms
Week - 10	Support Vector Machines for Classification Problems
Week - 11	Hidden Markov Models
Week - 12	Unsupervised Learning Algorithms

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