Course Information

Course Name	Turkish	Veriden Öğrenme
	English	Learning From Data
Course Code	BLG 454E	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	-	3	3	-	-
Course Language		English
Course Coordinator		Yusuf Yaslan
Course Objectives		Introduce students to major data analytics and machine learning methods and underlying theories - Learning to apply available tools to solve classification, clustering and regression problems - Learning to avoid major pitfalls such as overfitting, confusing correlation and causality while using machine learning tools - Learning the assessment and comparison of performance of machine learning methods
Course Description		Introduction to Machine Learning, major applications Mathematical background, marginal and conditional Probability, Bayes theorem, Bayesian decision theory Density estimation, Maximum Likelihood estimate, Bayesian Learning, Naïve Bayes Linear regression Bias-variance dilemma, regularization, ridge regression and lasso Linear classifiers Artificial neural networks, perceptron and multilayer perceptron Assessment and comparison of classifier performance Feature selection and extraction Large margin classifiers, support vector machines, kernel methods Decision trees and random forest Unsupervised learning, clustering Deep learning and big data
Course Outcomes
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