COMP321

Practical Data Mining

This paper is a practical introduction to data mining. It covers important aspects of the data mining process such as feature selection, model building, parameter tuning and final evaluation.

COMP321 - 18B (HAM) & 18B (TGA)

20.0 Points

This paper is a practical introduction to data mining. It covers important aspects of the data mining process such as feature selection, model building, parameter tuning and final evaluation.

Prerequisite(s): (COMP103 or ENGG182) and 20 points at 200 level in Computer Science

Restriction(s): STAT321

Internal assessment/examination ratio: 2:1

Timetabled Lectures

The Timetable for 2018 is not available.

Indicative Fees

Fees for 2018 are not yet available.

Paper Outlines

The following 2017 paper outlines are available for COMP321. Please contact the Faculty or School office for details on 2018 outlines.

Available Subjects:  Computer Science | Applied Computing | Data Analytics | Statistics

Other available years: Practical Data Mining - COMP321 (2017)

Paper details current as of : 13 September 2017 5:00pm
Indicative fees current as of : 20 September 2017 4:30am

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