CSCI 358 Machine Learning
3 hours
This course focuses on machine learning - a collection of techniques for extracting useful information from data. This information is commonly used to make predictions. Students learn how many companies use predictive analytics for calculating or identifying such information as credit scores, real estate values, social connections, online behavior, and/or financial performance. Students will also understand how some applications of machine learning can be loaded with ethical implications such as the prediction of criminality, gene expression, credit worthiness and/or job effectiveness. In this course students will focus on understanding and applying basic issues and techniques in machine learning such as overfitting, linear models, validation, and standard algorithms. Students will primarily study supervised learning, though the course will also investigate unsupervised methods (for example clustering) toward the end of the semester.