Learning and Reasoning with Bayesian Networks

Lecture, four hours; discussion, two hours; outside study, six hours. Requisite: course 112 or Electrical Engineering 131A. Review of several formalisms for representing and managing uncertainty in reasoning systems; presentation of comprehensive description of Bayesian inference using belief networks representation. Letter grading.

Review Summary

Clarity
10.0 / 10
Organization
10.0 / 10
Time
5-10 hrs/week
Overall
10.0 / 10

Reviews

    Quarter Taken: Winter 2022 In-Person
    Grade: A-

    One of the best CS professor in UCLA. the course is will organized. There are recorded lectures from previous years. There will be a midterm exam and a final exam. Weekly assignments for each week.

Course

Instructor
Adnan Darwiche
Previously taught
23W 22W

Grading Information

  • No group projects

  • Attendance not required

  • 1 midterm

  • Finals week final

  • 100% recommend the textbook

Previous Grades

Grade distributions not available.

Textbooks

Textbook information not available.