CS-22828 Machine learning theory

This course offers a comprehensive overview of machine learning and statistical pattern recognition, covering topics such as supervised learning (including generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines), unsupervised learning (encompassing clustering, dimensionality reduction, kernel methods), and learning theory.