Advanced Machine Learning

Catalog description

Advanced Machine Learning (3) This course explores state-of-the-art developments in machine learning and artificial intelligence (AI), emphasizing both theoretical foundations and practical applications. Topics include generative adversarial networks (GANs), graph neural and representation networks, and tensor/matrix factorization methods. Students study the mathematical principles behind these models and derive their corresponding optimization algorithms, gaining a deep understanding of how modern AI systems learn from complex and high-dimensional data. The course highlights cutting-edge applications of advanced machine learning across domains such as natural language processing, social and political analytics, and scientific discovery. Crosslist: DATA-642. Prerequisite: STAT-427.