IntroductionProbabilistic approach in machine and deep learning leads to principled solutions. It provides explainable decisions and new ways for improving of existing approaches. Bayesian machine learning consists of probabilistic approaches that rely on Bayes formula. It can help in numerous applications and has beautiful mathematical concepts behind. In this course, I will describe the found...
PrerequisiteProbability theory, Mathematical statistics, Machine learningAbstractMachine learning considers many models. Some are interpretable, others are probabilistic, and others are used in practice. Gaussian process-based models have all these properties: they are interpretable, probabilistic, and lead to practical solutions. The history of applications of Gaussian process regression in ma...