- Code COMP3670
- Unit Value 6 units
Essential foundations for any machine learning application are a basic statistical analysis of the data to be processed, a solid understanding of the mathematical foundations underpinning machine learning as well as the basic classes of learning/adaptation concepts. Those foundations are bundled in this single, introductory course to machine learning in preparation for deeper explorations into the topic, but also as a standalone unit.
Upon successful completion, students will have the knowledge and skills to:
- Develop an appreciation for what is involved in learning from data
- Understand basic data wrangling and data exploration
- Describe a variety of machine learning tasks: clustering, dimensionality reduction, regression and classification
- Understand how to formalise practical problems in terms of above tasks
- Interpret mathematical equations from linear algebra, calculus, statistics, and probability theory in terms of machine learning methods
- Understand how to perform evaluation of learning algorithms and model selection in practical problems
- Assignment (40) [LO null]
- Final Exam (60) [LO null]
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Up to 60 hours of total face-time, which includes interactions with lectures and tutors. Up to 60 hours of total preparation, repeat, assignment and practical exercise time.
Requisite and Incompatibility
Tuition fees are for the academic year indicated at the top of the page.
Commonwealth Support (CSP) Students
If you have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). More information about your student contribution amount for each course at Fees.
- Student Contribution Band:
- Unit value:
- 6 units
If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
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Offerings, Dates and Class Summary Links
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery||Class Summary|
|7396||25 Jul 2022||01 Aug 2022||31 Aug 2022||28 Oct 2022||In Person||N/A|