Foundations of Statistics & Machine Learning

3 credits

Statistical basis for machine learning. Topics include distributions, probabilities, sampling, hypothesis testing, Bayes’ theorem, maximum likelihood, machine learning theory, classes of machine learning, linear regression, kernel methods, dimensional reduction, gradient descent, ensemble techniques, and neural networks. A laboratory component is required. *Note: Students may receive credit for one of CS 712 or STAT 712.*