Machine Learning is commonly considered to be a sub-field of Artificial Intelligence, and can be seen as the study of computational approaches to finding patterns in data. This unit extends the treatment of the topic beyond that in its prerequisite unit, both in breadth, through an introduction to Reinforcement Learning, and in depth through a discussion of research papers from the literature. It also introduces the application of Machine Learning techniques in the area of (2D) computer vision and the use of image processing techniques as a precursor to the application of Machine Learning.
TEACHING PATTERN: 3 lectures / seminars weekly and (for most of semester) 1 tutorial weekly
FLEXIBLE & ONLINE STUDY OPTIONS Note: Class attendance may still be required
Web dependent -
H,L
Some parts of this unit will be taught online
Video conferencing -
H,L
A live video link between campuses is used for at least some teaching in this unit
About Flexible Study Options
Units are offered in attending mode unless otherwise indicated (that is attendance is required at the campus identified). A unit identified as offered by distance, that is there is no requirement for attendance, is identified with a nominal enrolment campus. A unit offered to both attending students and by distance from the same campus is identified as having both modes of study.
Campus - H Hobart, L Launceston, W Burnie. Study Centre - V Sydney, R Rozelle, P Beauty Point. Distance units may also have a campus identifier of I Isolated, N Interstate, O Overseas. Units delivered in Transnational Education (TNE) Programs have a campus identifier of A Hangzhou, F Fuzhou, G Shanghai, K KDU Malaysia, Q Kuwait or Y Hong Kong.
Special approval is required for enrolment into TNE Program units - campuses A, F, G, K, Q and Y click here for more information.
Web dependent -
H,L
