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SPECIAL STUDIES
2021 Spring Term
1-3 Units
Computer Science 796
Group activity. Not offered regularly in the curriculum but which is offered on topics selected on the basis of timeliness, need and interest, and generally in the format of regularly scheduled bulletin offerings.
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 3080
3 Units
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01/19 - 05/07
(1)
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Th 5:00 PM - 7:30 PM
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Athula Gunawardena
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 MG0125
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MATRIX METH./DATA MINING
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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.
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PREREQ: ADMISSION TO GRADUATE PROGRAM IN COMPUTER SCIENCE
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