Engineering Data Analytics (3.0 units)
Theory and methods of data analytics emphasizing engineering applications: multivariate statistics, supervised learning, classification, smoothing and kernel methods, support vector machines, discrimination analysis, unsupervised learning.
- Crosslist: This course is offered by the ISE department but may qualify for major credit in INF. To register, enroll in ISE 529.
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|Cesar Acosta-Mejia||KAP156||PDF (473686 KB)|