PhDAI 731 - Analytical Methods for Machine Learning

Credit(s): 3 hours
This course explores the analytical and mathematical techniques underpinning modern machine learning models. Students will engage with topics such as linear algebra, probability theory, multivariate calculus, and optimization algorithms, which are crucial for understanding machine learning systems’ design, training, and evaluation. Through a combination of theoretical insights and practical exercises, learners will build a solid foundation in the analytical skills required to address real-world machine learning challenges and enhance the performance of AI models.
Prerequisite(s): PhDAI 730 - Statistics for AI