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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?
Study level | Postgraduate |
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Academic unit | Computer Science |
Credit points | 6 |
Prerequisites:
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None |
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Corequisites:
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COMP5318 or COMP4318 or COMP3308 or COMP3608 |
Prohibitions:
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COMP4328 or OCMP5328 |
Assumed knowledge:
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None |
At the completion of this unit, you should be able to:
This section lists the session, attendance modes and locations the unit is available in. There is a unit outline for each of the unit availabilities, which gives you information about the unit including assessment details and a schedule of weekly activities.
The outline is published 2 weeks before the first day of teaching. You can look at previous outlines for a guide to the details of a unit.
Session | MoA ? | Location | Outline ? |
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Semester 2 2024
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Normal evening | Camperdown/Darlington, Sydney |
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Session | MoA ? | Location | Outline ? |
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Semester 2 2025
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Normal evening | Camperdown/Darlington, Sydney |
Outline unavailable
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Session | MoA ? | Location | Outline ? |
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Semester 2 2020
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Normal evening | Camperdown/Darlington, Sydney |
View
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Semester 2 2021
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Normal evening | Remote |
View
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Semester 2 2022
|
Normal evening | Camperdown/Darlington, Sydney |
View
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Semester 2 2022
|
Normal evening | Remote |
View
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Semester 2 2023
|
Normal evening | Camperdown/Darlington, Sydney |
View
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Find your current year census dates
This refers to the Mode of attendance (MoA) for the unit as it appears when you’re selecting your units in Sydney Student. Find more information about modes of attendance on our website.