Machine learning is the practice of programming computers to learn and improve through experience, and it is becoming pervasive in technology and science. This course will cover the mathematical underpinnings, algorithms, and practices that enable a computer to learn. Topics will include supervised learning, unsupervised learning, and the evaluation of learning algorithms. Students will write computer programs and apply course skills to solve real-world prediction and pattern recognition problems.
Prerequisites: COMP 241 and MATH 112 or MATH 115 or MATH 116