Code |
Course Name |
Language |
Type |
END 476E |
Machine Learning for Industrial Systems |
English |
Elective |
Local Credits |
ECTS |
Theoretical |
Tutorial |
Laboratory |
3 |
4 |
3 |
0 |
0 |
Course Prerequisites and Class Restriction |
Prerequisites |
(END 311 MIN DD or END 311E MIN DD or ECN 211E MIN DD or ECN 209E MIN DD) and (MAT 210 MIN DD or MAT 210E MIN DD or END 210 MIN DD or END 210E MIN DD or ECN 207E MIN DD)
|
Class Restriction |
None |
Course Description |
Machine learning concepts, linear regression, logistic regression, decision trees, k-means clustering, Gaussian
Mixture Models, k- nearest neighbors, artificial neural networks, deep learning, support vector machines, hybrid
methods, overfitting, cross validation, parameter optimization. |
|