Search Results

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.

Fall 2017: COMS W4771
Course Number Section/Call Number Times/Location Instructor Points Enrollment
COMS 4771 001/76261 M W 2:40pm - 3:55pm
428 Pupin Laboratories
James McInerney 3 88/130
COMS 4771 002/11548 T Th 2:40pm - 3:55pm
207 Mathematics Building
Nakul Verma 3 132/152
COMS 4771 H01/80532  
James McInerney 3 34/50
Spring 2018: COMS W4771
Course Number Section/Call Number Times/Location Instructor Points Enrollment
COMS 4771 001/21286 M W 1:10pm - 2:25pm
501 Northwest Corner
Nakul Verma 3 0/130
COMS 4771 002/67785 M W 2:40pm - 3:55pm
501 Northwest Corner
Nakul Verma 3 0/130