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.
Unit details and rules
Academic unit | Computer Science |
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Credit points | 6 |
Prerequisites
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None |
Corequisites
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None |
Prohibitions
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COMP5318 or COMP4318 |
Assumed knowledge
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Experience with programming and data structures as covered in COMP2123 or COMP2823 or COMP9123 (or equivalent unit of study from different institutions) |
Available to study abroad and exchange students | No |
Teaching staff
Coordinator | Nataliia Stratiienko, nataliia.stratiienko@sydney.edu.au |
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