MATRIX METHODS IN DATA MINING AND PATTERN RECOGNITION
MATRIX METHODS IN DATA MINING AND PATTERN RECOGNITION
2023 Spring Term
3 Units
Computer Science 739
This course focuses on matrix methods in data mining and pattern recognition, and features real-world applications ranging from classification and clustering to denoising and data analysis. The topics covered include: linear equations, regression, regularization, the singular value decomposition, iterative algorithms, classification using singular value decomposition bases, tangent distance, latent semantic indexing, clustering, support vector machines, and random walk and Markov chains.
Other Requirements: PREREQ: ADMISSION TO GRADUATE PROGRAM IN COMPUTER SCIENCE
Class Schedule
Disclaimer
- This schedule is informational and does not guarantee availability for registration.
- Sections may be full or not open for registration. Please use WINS if you wish to register for a course.
| Section Details | Meeting Details & Topic | Instructor | Syllabus | ||
|---|---|---|---|---|---|
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01-LEC 3245
3 Units
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01/23 - 05/06 (1) | W 5:00 PM - 7:30 PM |
Athula Gunawardena
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