Principled Machine Learning

We introduce the underlying concepts which give rise to some of commonly used machine learning methods, excluding deep-learning machines and neural networks. point their advantages, limitations potential use in various areas photonics. The main methods covered include parametric non-parametric regression classification techniques, kernel-based support vector machines, decision trees, probabilistic models, Bayesian graphs, mixture Gaussian processes, message passing visual informatics.