Machine learning models explain and generalise data. This course introduces some fundamental machine learning concepts, learning problems and algorithms to provide understanding and simple answers to many questions arising from data explanation and generalisation. For example, why do different machine learning models work? How to further improve them? How to adapt them to different purposes? The fundamental concepts, learning problems and algorithms are carefully selected. Many of them are closely related to practical questions of the day, such as transfer learning, learning with label noise and multi-view learning.
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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COMP5318 OR COMP3308 OR COMP3608 |
Prohibitions
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None |
Assumed knowledge
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None |
Available to study abroad and exchange students | No |
Teaching staff
Coordinator | Tongliang Liu, tongliang.liu@sydney.edu.au |
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