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Unit of study_
COMP4329: Deep Learning
This course provides an introduction to deep machine learning, which is rapidly emerging as one of the most successful and widely applicable set of techniques across a range of applications. Students taking this course will be exposed to cutting-edge research in machine learning, starting from theories, models, and algorithms, to implementation and recent progress of deep learning. Specific topics include: classical architectures of deep neural network, optimization techniques for training deep neural networks, theoretical understanding of deep learning, and diverse applications of deep learning in computer vision.
| Code | COMP4329 |
|---|---|
| Academic unit | Computer Science |
| Credit points | 6 |
|
Prerequisites:
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|
COMP3308 or COMP3608 or COMP4318 or BMET2925 |
|---|---|
|
Corequisites:
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Enrolment in a thesis unit. INFO4001 or INFO4911 or INFO4991 or INFO4992 or AMME4111 or BMET4111 or CHNG4811 or CIVL4022 or ELEC4712 or COMP4103 or SOFT4103 or DATA4103 or ISYS4103 |
| Prohibitions:
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COMP5329 OR OCMP5329 |
The learning outcomes for this unit will be available two weeks before the first day of teaching.
Unit outlines
Unit outlines will be available 1 week before the first day of teaching for the relevant session.
- Semester 1, 2023 [Normal evening] - Camperdown/Darlington, Sydney
- Semester 1, 2023 [Normal evening] - Remote
There are no unit outlines available online for previous years.
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