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COMS W4771 Machine Learning. 3 points.
Lect: 3.
Prerequisites: Any introductory course in linear algebra and any introductory course in statistics are both required. Highly recommended: COMS W4701 or knowledge of Artificial Intelligence.
Topics from generative and discriminative machine learning including least squares methods, support vector machines, kernel methods, neural networks, Gaussian distributions, linear classification, linear regression, maximum likelihood, exponential family distributions, Bayesian networks, Bayesian inference, mixture models, the EM algorithm, graphical models and hidden Markov models. Algorithms implemented in MATLAB.
Spring 2021: COMS W4771
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4771 | 001/11934 | T Th 1:10pm - 2:25pm Online Only |
Nakul Verma | 3 | 95/110 |
COMS 4771 | 002/11935 | T Th 2:40pm - 3:55pm Online Only |
Nakul Verma | 3 | 74/110 |
COMS 4771 | V01/17804 | |
Nakul Verma | 3 | 7/99 |
Fall 2021: COMS W4771
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
COMS 4771 | 001/12498 | T Th 2:40pm - 3:55pm Room TBA |
Nakul Verma | 3 | 0/110 |
COMS 4771 | 002/12499 | T Th 1:10pm - 2:25pm Room TBA |
Daniel Hsu | 3 | 65/110 |
COMS 4771 | V01/17070 | |
Nakul Verma | 3 | 0/99 |