Course Information

Course Name	Turkish	İş Zekası ve Makine Öğrenimi Uygulamaları
	English	Business Intell.&Mac.Lear.App.
Course Code	END 574E	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	-	3	3	-	-
Course Language		English
Course Coordinator		Mehmet Güray Güler
Course Objectives		This course Introduces the main algorithms used in machine learning by providing the mathematical derivations and shows how to evaluate and choose the appropriate models.
Course Description		A general introduction to machine learning; methods of regression, classification, clustering, and dimensionality reduction; supervised and unsupervised models; linear and nonlinear models; parametric and nonparametric models; combinations of multiple models; comparisons of multiple models and model selection.
Course Outcomes		- understanding regression, classification, clustering, and dimensionality reduction algorithms - measuring the quality of models developed for problems and selecting models - applying these algorithms to real-world problems
Pre-requisite(s)		- Statistics - Linear algebra - Calculus (derivation, chain rule) - Nonlinear optimization (at least an introductory level) - Python (you will have computer assignments)
Required Facilities
Other
Textbook		ALPAYDIN, Ethem (2020). Introduction to machine learning. MIT press James, G., Witten, D., Hastie, T., Tibshirani, R., & Taylor, J. (2023). An introduction to statistical learning: With applications in python. Springer Nature.
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