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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.

Summer 2018: COMS W4771
Course Number Section/Call Number Times/Location Instructor Points Enrollment
COMS 4771 D01/77621  
Nakul Verma 3 8
Fall 2018: COMS W4771
Course Number Section/Call Number Times/Location Instructor Points Enrollment
COMS 4771 001/67443 M W 2:40pm - 3:55pm
301 Pupin Laboratories
Nakul Verma 3 138/155
COMS 4771 002/13758 M W 10:10am - 11:25am
451 Computer Science Bldg
Daniel Hsu 3 51/110
Spring 2019: COMS W4771
Course Number Section/Call Number Times/Location Instructor Points Enrollment
COMS 4771 001/19903 M W 1:10pm - 2:25pm
451 Computer Science Bldg
Nakul Verma 3 0/110
COMS 4771 002/23303 M W 2:40pm - 3:55pm
451 Computer Science Bldg
Nakul Verma 3 0/110
COMS 4771 V01/29514 M W 1:10pm - 2:25pm
Room TBA
Nakul Verma 3 8