Advanced Statistical Methods

Catalog description

Statistics is used in computer algorithms (machine learning) to enhance computer decision-making and prediction capabilities. this course will cover a wide variety of topics in statistical learning methods. Major statistical methods used in machine learning such as linear regression, survival analysis, and others will be discussed. Additional topics include unsupervised learning and supervised techniques such as principal component analysis, nearest neighbor, random forest, support vector machines, and neural networks. Simulation methods, such as the EM algorithm, Metropolis-Hasting algorithm, and the Markov Chain Monte Carlo method will also be discussed. Enrollment is limited to Graduate level students.