Useful links
Machine learning is the process of automatically building mathematical models that explain and generalise datasets. It integrates elements of statistics and algorithm development into the same discipline. Data mining is a discipline within knowledge discovery that seeks to facilitate the exploration and analysis of large quantities for data, by automatic and semiautomatic means. This subject provides a practical and technical introduction to machine learning and data mining. Topics to be covered include problems of discovering patterns in the data, classification, regression, feature extraction and data visualisation. Also covered are analysis, comparison and usage of various types of machine learning techniques and statistical techniques.
Code | COMP5318 |
---|---|
Academic unit | Computer Science |
Credit points | 6 |
Prerequisites:
?
|
None |
---|---|
Corequisites:
?
|
None |
Prohibitions:
?
|
COMP4318 OR OCMP5318 |
Assumed knowledge:
?
|
Experience with programming and data structures as covered in COMP2123 OR COMP2823 or COMP9123 (or equivalent unit of study from different institutions). |
At the completion of this unit, you should be able to:
Unit outlines will be available 1 week before the first day of teaching for the relevant session.
Key dates through the academic year, including teaching periods, census, payment deadlines and exams.
Enrolment, course planning, fees, graduation, support services, student IT
Code of Conduct for Students, Conditions of Enrollment, University Privacy Statement, Academic Integrity
Academic appeals process, special consideration, rules and guidelines, advice and support
Policy register, policy search
Scholarships, interest free loans, bursaries, money management
Learning Centre, faculty and school programs, Library, online resources
Student Centre, counselling & psychological services, University Health Service, general health and wellbeing