Nov 29, 2020  
2020-2021 Undergraduate Catalog 
    
2020-2021 Undergraduate Catalog
Add to Portfolio (opens a new window)

CS 4267:Machine Learning

3 Class Hours 0 Laboratory Hours 3 Credit Hours
Prerequisite: CS 3642  
This course provides a broad introduction to machine learning and statistical pattern recognition including supervised, unsupervised, and ensemble learning. Topics include K-NN, Naïve Bayes Classifier, parametric and non-parametric methods, support vector machines, kernel machines, neural networks, clustering, dimensionality reduction, and model evaluation. The learning theory including bias/variance tradeoffs and large margins will be introduced. This course will also discuss recent applications of machine learning such as data mining, autonomous navigation, speech recognition, and text and web data processing.



Add to Portfolio (opens a new window)