Machine Learning and Pattern Recognition

The course is an introduction to the theoretical foundations of machine learning. A variety of classical and recent results in machine learning and statistical analysis are discussed, including: Bayesian classification, regression, regularization, sparse regression, support vector machines, kernels, neural networks and gradient descent.