CS 5780: Empirical Methods in Machine Learning and Data MiningCross-Listing: Not cross-listed. This implementation-oriented course presents a broad introduction to current algorithms and approaches in machine learning, knowledge discovery, and data mining and their application to real-world learning and decision-making tasks. The course also covers experimental methods for comparing learning algorithms, for understanding and explaining their differences, and for exploring the conditions under which each is most appropriate. Offered: Fall only Prerequisites: CS 2800 and CS 3110, or the equivalent. Grade options: Letter or S/U Credit hours: 4 Recent offerings:
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