CS 38300 - Machine Learning

This course is an introduction to both theory and applications in machine learning. The topics include the fundamentals of machine learning, end-to-end machine learning projects, and popular machine learning methods and technologies, such as linear regression, gradient descent, polynomial regression, logistic regression, support vector machines, decision tree, random forest, artificial neural networks, convolutional neural networks, recurrent neural networks, reinforcement learning, and unsupervised learning techniques.

Preparation for Course
P: CS 26000 with a grade of C or better, and either STAT 51100 or STAT 30100.

Cr. 3.
Student Learning Outcomes