Data streams are everywhere, from F1 racing over electricity networks to news feeds. Data stream mining relies on and develops new incremental algorithms that process streams under strict resource limitations.
|Prerequisite(s):||COMPX305 or COMPX310 or COMP316 or COMP321 and a further 30 points at 300 level in Computer Science|
|Internal assessment / examination:||100:0|
Trimesters and Locations
|Occurrence Code||When taught||Where taught|
|20A (HAM)||A Trimester : 2 Mar 2020 - 28 Jun 2020||Hamilton|
Timetabled Lectures for Data Stream Mining (COMPX523)
|Mon||9:00 AM||10:00 AM||G.1.15||Mar 2 - May 17|
|Thu||10:00 AM||11:00 AM||G.1.15||Mar 2 - May 17|
NB:There may be other timetabled events for this paper such as tutorials or workshops.
Visit the online timetable for COMPX523 for more details
Indicative Fees for Data Stream Mining (COMPX523)
Paper Outlines for Data Stream Mining (COMPX523)
The following paper outlines are available for Data Stream Mining (COMPX523).
If your paper occurrence is not listed contact the Faculty or School office.
Other available years: Data Stream Mining - COMPX523 (2019)
Paper details current as of : 1 July 2020 8:51am
Indicative fees current as of : 4 June 2020 3:25pm