Machine Learning: 3 semester hours

Catalog description

Topics cover fundamental machine learning algorithms and paradigms including information-based learning, probability-based learning, instance-based learning, error-based learning, neural networks and deep learning, unsupervised learning, etc. Focus on implementation and data visualization using modern programming languages such as Python and R. Prerequisites: ( COMP 2336 or COMP 2103) or (COMP 2013 or COMP 2336 ).