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Unit of study_

OCMP5318: Machine Learning and Data Mining

Machine learning is the process of automatically building mathematical models that explain and generalise datasets. It integrates elements of statistics and algorithm development into the same discipline. Data mining is a discipline within knowledge discovery that seeks to facilitate the exploration and analysis of large quantities for data, by automatic and semiautomatic means. This subject provides a practical and technical introduction to machine learning and data mining. Topics to be covered include problems of discovering patterns in the data, classification, regression, feature extraction and data visualisation. Also covered are analysis, comparison and usage of various types of machine learning techniques and statistical techniques.

Code OCMP5318
Academic unit Computer Science
Credit points 6
Prerequisites:
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None
Corequisites:
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None
Prohibitions:
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COMP5318 or COMP4318
Assumed knowledge:
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Experience with programming and data structures as covered in COMP2123 or COMP2823 or COMP9123 (or equivalent unit of study from different institutions)

At the completion of this unit, you should be able to:

  • LO1. Students will be able to describe the basic principles, strengths, weaknesses and applicability of machine learning algorithms for solving classification, regression, clustering and reinforcement learning tasks.
  • LO2. Students will be able to design machine learning algorithms through practical experience in designing, implementing and evaluation machine learning algorithms.
  • LO3. Students will be able to design machine learning algorithms for solving classification, regression, clustering, and reinforcement learning tasks using machine learning software and libraries.
  • LO4. Students will be able to present and interpret data and information in verbal and written form.

Unit outlines

Unit outlines will be available 1 week before the first day of teaching for the relevant session.

There are no unit outlines available online for previous years.