— Machine Learning & Discovery

Prerequisites & course information

Course Description: Artificial intelligence techniques for knowledge acquisition by computers. Fundamental problems in machine learning and discovery. Systems that learn from examples, analogies, and solved problems. Systems that discover numerical laws and qualitative relationships. Projects centering on implementation and evaluation. Learning Activities: Lecture 3 hour(s), Project 1 hour(s). Enrollment Restriction(s): Pass One open to PhD students in Computer Science only and Pass Two open to graduate students in Computer Science only. Grade Mode: Letter. Learning Activities: Lecture 3 hour(s), Project 1 hour(s). Enrollment Restriction(s): Pass One open to PhD students in Computer Science only and Pass Two open to graduate students in Computer Science only. Grade Mode: Letter.