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Search Results
| Name | Grades | Rating | |||
|---|---|---|---|---|---|
Not teaching in Spring 2026 | |||||
EESC 6364 (Overall) | |||||
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EESC 6364 Nasser Kehtarnavaz | |||||
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Search Results
| Name | Grades | Rating | |||
|---|---|---|---|---|---|
Not teaching in Spring 2026 | |||||
EESC 6364 (Overall) | |||||
A- | |||||
EESC 6364 Nasser Kehtarnavaz | |||||
A- | |||||
Machine Learning and Pattern Recognition
EESC 6364
Erik Jonsson School of Engineering and Computer Science
This course covers basic concepts and algorithms for pattern recognition and machine learning. Bayesian decision theory, parametric learning, non-parametric learning, linear regression, linear classifiers and support vector machine, kernel methods, data clustering, mixture models, component analysis, multilayer neural networks, and deep learning with convolutional neural networks. 3 credit hours.
Prerequisites: Knowledge of probability and knowledge of MATLAB or C.
Offering Frequency: Every two years
Grades: 92
Median GPA: A-
Mean GPA: 3.392
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Machine Learning and Pattern Recognition
EESC 6364
Erik Jonsson School of Engineering and Computer Science
This course covers basic concepts and algorithms for pattern recognition and machine learning. Bayesian decision theory, parametric learning, non-parametric learning, linear regression, linear classifiers and support vector machine, kernel methods, data clustering, mixture models, component analysis, multilayer neural networks, and deep learning with convolutional neural networks. 3 credit hours.
Prerequisites: Knowledge of probability and knowledge of MATLAB or C.
Offering Frequency: Every two years
Grades: 92
Median GPA: A-
Mean GPA: 3.392
Click a checkbox to add something to compare.