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IE 451 Data Visualization and Analysis
Introduction to data analytics and information visualization; methods and metrics for validation; bias-variance trade- off; data visualization and understanding; data preprocessing; supervised learning (classification and regression); unsupervised learning; association rule mining; feature subset selection; metaheuristics; PCA; ANN and Multilayer Perceptron.
SU Credits : 3.000
ECTS Credit : 6.000
Prerequisite : -
Corequisite : -