Statistical Learning for Big Data: 3 semester hours

Catalog description

This course focuses on principles and best practices of machine learning from a probabilistic perspective with a strong tilt towards applications in big data analytics. It will cover various aspects of statistical learning theory, theory of generalization, overfitting and regularization, validation and cross-validation. It will also cover linear classifiers, linear regression, logistic regression and nonlinear transformations, neural networks and support vector machines.