— Recommender Systems

Prerequisites & course information

Course Description: Collaborative filtering and content-based methods for building recommender systems. Statistical, matrix factorization, textual analysis, and nearest-neighbor approaches. Case studies. Learning Activities: Lecture 3 hour(s), Discussion 1 hour(s). Enrollment Restriction(s): Pass One restricted to Computer Science and Computer Science & Engineering students only. Grade Mode: Letter. General Education: Science & Engineering (SE). Learning Activities: Lecture 3 hour(s), Discussion 1 hour(s). Enrollment Restriction(s): Pass One restricted to Computer Science and Computer Science & Engineering students only. Grade Mode: Letter. General Education: Science & Engineering (SE).