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)	PROFESÖR DOKTOR SERKAN GÜNAL
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.
Required or Recommended Resources	Ethem Apaydin, Introduction to Machine Learning, 2e. The MIT Press, 2010.
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	Quality Education , Industry, Innovation and Infrastructure

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
Homework	1	30
Final Exam	1	40
Toplam (%)		100