Subject description
Introduction to Data Mining, Knowledge Discovery, and Big Data with coverage of Data Structures, role of Data Quality and per-processing, Association Rules, Artificial Neural Networks, Support Vector methods, Tree Based Methods, Clustering and Classification Methods, Regression and Statistical Methods, Overfitting and Inferential issues, Evaluation, Use of Data Mining packages with … For more content click the Read More button below.
Enrolment rules
Pre-Requisite
Equivalence
INFO911 - Data Mining and Knowledge Discovery
Delivery
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Work integrated learning
Embedded WIL:This subject contains elements of "Embedded WIL". Students in this subject will experience activities that relate to or simulate professional practice as part of their learning.
Textbook information
No prescribed textbooks for this subject.