C_S 5455 - Topics in Machine Learning (3)

When Offered: Fall, Even-numbered years
Machine Learning is the process of teaching a computer what to do by providing a model for learning and many examples but without explicit instructions. This course uses computer programming and linear algebra to understand machine learning algorithms, their practical application, and ways to evaluate them. Topics include machine learning models such as artificial neural networks and support vector machines, as well as techniques such as feature selection, dimensionality reduction, model selection, and hyperparameter tuning.
Prerequisites: CS 3460 (Data Structures) and MAT 2240 (Linear Algebra)