CMPE 333 Data Analytics
CMPE 333 Data Analytics Units: 3.00
Introduction to data analytics; data preparation; assessing performance; prediction methods such as decision trees, random forests, support vector machines, neural networks and rules; ensemble methods such as bagging and boosting; clustering techniques such as expectation-maximization, matrix decompositions, and biclustering; attribute selection.
COURSE DELETED 2017-2018
(Lec: 3, Lab: 0, Tut: 0)
Offering Term: W
CEAB Units:
Mathematics 10
Natural Sciences 0
Complementary Studies 0
Engineering Science 14
Engineering Design 12
Offering Faculty: Faculty of Arts and Science