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Curricular information is subject to change
On completion of this module, students will be able to:
1) Distinguish between the different categories of machine learning algorithms;
2) Identify a suitable machine learning algorithm for a given application or task;
3) Run and evaluate the performance of a range of algorithms on real datasets using Python libraries.
|Student Effort Type||Hours|
|Autonomous Student Learning||
Not applicable to this module.
|Description||Timing||Component Scale||% of Final Grade|
|Assignment: Machine Learning Exercise||Week 9||n/a||Alternative linear conversion grade scale 40%||No||
|Examination: End of semester exam||1 hour End of Trimester Exam||No||Alternative linear conversion grade scale 40%||No||
|Assignment: Machine Learning exercise||Week 6||n/a||Alternative linear conversion grade scale 40%||No||
|Resit In||Terminal Exam|
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
Not yet recorded.