- Schedule of Classes - October 20, 2018 7:14PM EDT
- Course Catalog - October 20, 2018 7:15PM EDT
Course information provided by the Courses of Study 2018-2019.
This course covers the basic concepts, models and algorithms of statistical inference, supervised learning, unsupervised learning, and artificial neural networks. Application topics include process monitoring, fault diagnosis, root cause analysis, quality control, machine learning for process optimization, data-driven decision making under uncertainty, machine learning for materials screening, chemical property estimation, missing data imputation, anomaly detection, data de-noising, and outlier detection.
When Offered Spring.
Prerequisites/Corequisites Prerequisite: Basic probability (CEE 3040/MATH 4710/ORIE 3500 or equivalent) and optimization (CHEME 6800/SYSEN 6800, ORIE 3310/ORIE 5310, or ORIE 5380).
Credits and Grading Basis
4 Credits GradeNoAud(Letter grades only (no audit))
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