MATH 5310 - Machine Learning

Credit Hours 3
Cross Listed: STAT 5310 & MATH 4310
Prerequisite: Admission to the MS or PSM in Computer Science and Quantitative Methods or instructor permission
Description: This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, deep learning); learning theory and best practices for applying machine learning algorithms to areas including computer vision, text processing, and bioinformatics.