ITCS 5356 - Introduction to Machine Learning

Machine learning has been successfully applied to many different areas such as autonomous control of cars and robots, natural language processing, image recognition, health science, biology, and data mining. This course introduces fundamental concepts and methods to learn from data for computational data analysis, including pattern recognition, prediction, and visualization. For this, this course covers supervised learning, unsupervised learning, and reinforcement learning, including linear regression, perceptron, k-Nearest Neighbor, logistic regression, clustering, dimensionality reduction, reinforcement learning, and neural networks based on the foundations of linear algebra, probability theory, and optimization.

Credit Hours: (3)

Schedule of Classes