Mahdi Milani Fard
Term: Fall 2013.
When: Monday / Wednesday, 2:30-4:00pm
Course schedule (including lecture slides, homeworks, solutions.)
The course will cover selected topics and new developments in data mining and applied machine learning, with a particular emphasis on good methods and practices for effective deployment of real systems. We will study commonly used algorithms and techniques, including linear and logistic regression, clustering, neural networks, support vector machines, decision trees and more. We will also discuss methods to address practical issues such as feature selection and dimensionality reduction, error estimation and empirical validation, algorithm design and parallelization, and handling of large datasets. Important note:Students who took COMP-652 in 2012 or before CANNOT take COMP-598. However students will be able to take both COMP-598 in Fall 2013 and COMP-652 in Winter 2014. Contents of both courses have been designed to avoid too much overlap. COMP-598 focuses on the practical application of machine learning, whereas COMP-652 (Winter 2014 edition) will focus on theoretical analysis of machine learning, reinforcement learning, bandits and analysis of time series.