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.
|Academic unit||Computer Science|
|COMP3308 or COMP3608 or COMP4318 or BMET2925|
|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|
|COMP5329 OR OCMP5329|
The learning outcomes for this unit will be available two weeks before the first day of teaching.
Unit outlines will be available 1 week before the first day of teaching for the relevant session.