[USU] Introduction to Machine Learning

Students are able to master basic mathematical and computational tools used by the machine learning methods. Students possess knowledge regarding vectors, matrices, and linear algebra considering real-world applications of machine learning methods. Students understand mathematical principles for selected supervised (regression and classification) and unsupervised methods. Student know how to properly prepare input data, know various types of loss functions and their role in the training of models. Students know and understand concepts like regularization, methods for model validation, and ways how to handle outliers. Students are able to create simple implementations of methods and run numerical experiments on data from various domains.