LARGE-SCALE MACHINE LEARNING
Learning from large dataset is becoming a ubiquitous phenomena in all applications spanning robotics, medical decisions, internet, communication, biology, etc. Designed to give senior UG students a thorough grounding in the theory and algorithms needed for research and practical applications in machine learning for modern massive datasets. Topics draw from machine learning, classical statistics, algorithms and information theory. Graduate/Undergraduate Equivalency: COMP 542 . Mutually Exclusive: Cannot register for COMP 441 if student has credit for COMP 542 .
Prerequisites & course information
Short Title: LARGE-SCALE MACHINE LEARNING Department: Computer Science Grade Mode: Standard Letter Course Type: Lecture Credit Hours: 3 Restrictions: Enrollment is limited to Undergraduate, Undergraduate Professional or Visiting Undergraduate level students. Course Level: Undergraduate Upper-Level Prerequisite(s): COMP 440 or ELEC 440
Sources
- Course catalogue ↗2026–2027