Pattern Recognition (8240.2)
| Level: | Level 4 - Undergraduate Advanced Unit |
|---|---|
| Credit Points: | 3 |
| HECS Bands: | Band 2 2013-2020 (Expires 31 Dec 2020) Band 2 2021 (Commenced After 1 Jan 2021) Band 3 2021 (Commenced Before 1 Jan 2021) |
| Faculty: | Faculty of Education, Science, Technology & Maths |
| Discipline: | Academic Program Area - Maths & Technology |
CLOSED FOR FUTURE ENROLMENT.
Availability
Syllabus
This unit aims to provide students with an understanding or machine learning by studying methods to classify data (patterns) based either on a priori knowledge or on statistical information extract from those patterns. The patterns to be classified are usually groups of measurements or observations, defining points in an appropriate multidimensional space. This unit will also provide students with mathematical knowledge, including fuzzy logic and other skills, that are needed to support their concurrent and subsequent engineering studies.
Learning Outcomes
DESCRIPTION:
1.understand basic concepts of machine learning; understand basic mathematics and fuzzy logic and other necessary tools; carry out the basic techniques and algorithms using learned concepts such as face recognition, and other computer-aided diagnosis (CAD) systems;
2.understand an intriguing problem in pattern recognition is the relationship between the problem to be solved (data to be classified) and the performance of various pattern recognition algorithms (classifiers); apply the techniques and algorithms to solving problems and to mathematically model simple applications from engineering.
Contact Hours
up to 4 hours per week, 3L + 1T
Prerequisites
Software Technology 1 and Software Technology 2 and Object Oriented Software Design.