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System Optimisation & Machine Learning (ELEN90088) // Further information
Further information
- Texts
Prescribed texts
Recommended texts include:
"Convex Optimization" by Stephen Boyd and Lieven Vandenberghe, Cambridge University Press
"Pattern Recognition and Machine Learning" by Christopher Bishop, Springer
"Deep Learning" by Ian Goodfellow and Yoshua Bengio and Aaron Courville, MIT Press
- Subject notes
LEARNING AND TEACHING METHODS
The subject is designed and delivered using a project-based approach. Students complete a self-designed half-semester project in small teams in addition to two guided workshops in the first half. Teaching team facilitates productive team-work and project-progress in workshop sessions.INDICATIVE KEY LEARNING RESOURCES
Recorded and interactive lectures, discussion boards, consultation hours, and workshops along with reading suggestions provide students a wide range of resources for their theoretical and practical project-based learning.CAREERS / INDUSTRY LINKS
The subject covers topics modern and industry-relevant topics. Students also practice and advance their soft-skills such as report writing, presentation, project scoping. The subject is enriched by a guest lecture from industry every semester showcasing real-world applications of the material covered. - Related Handbook entries
This subject contributes to the following:
- Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 8 November 2024