This is a course on some methods of statistical inference, both from the classical and Bayesian branches of statistics. The topics include some basics in classical statistics, analysis of variance, multiple hypothesis testing, linear regression, Bayesian inference and Markov chain Monte Carlo for Bayesian computation. You can download the lecture notes for the course.
This is a course on Monte Carlo methods. You can download the lecture notes and the MATLAB code package for the course.
In Matematik Köyü, Şirince, İzmir, we have taught twice this small course on the mathematical fundamentals of machine learning. Slides for the Monte Carlo section are here (in Turkish). All the presented material can be downloaded here.
This course is in a very similar format with the ones in Matematik Köyü; however with more condensed lectures and richer application sessions. Slides for the Monte Carlo section are here (in Turkish). The github page for the course: here.
Didem Koçhan, MSc (co-supervised by Prof. Dr. İlker Birbil), Scalable Monte Carlo Inference In Regression Models With Missing Data, graduated in August 2018.
Hilal Tüysüz, MSc, Changepoint Model for Bayesian Online Fraud Detection in Call Data, graduated in August 2018.
Alara Güler, MSc (co-supervised by Prof. Dr. İlker Birbil), Applications of Bayesian Inference for the Origin-Destination Matrix Problem, graduated in January 2018.
Nurdan Kuru, PhD (supervised by Prof. Dr. İlker Birbil).
Vahid Tavakol, PhD (supervised by Prof. Dr. Ahmet Onat).
Serhat Emre Cebeci, MSc (supervised by Prof. Dr. Ahmet Onat).