COM SCI 262A
Learning and Reasoning with Bayesian Networks
Description: Lecture, four hours; outside study, eight 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.
Units: 4.0
Units: 4.0
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Most Helpful Review
Winter 2024 - Professor Darwiche definitely knows a lot about this subject, but I thought his lectures were pretty confusing to follow. There's a lot of slides and information he skips, and he tends to go back and forth between slides. Weekly homeworks were a lot of work, and the exams are pretty difficult as well. I'd only take it if you're really interested in learning about Bayesian Networks, as it is difficult and a decent amount of work
Winter 2024 - Professor Darwiche definitely knows a lot about this subject, but I thought his lectures were pretty confusing to follow. There's a lot of slides and information he skips, and he tends to go back and forth between slides. Weekly homeworks were a lot of work, and the exams are pretty difficult as well. I'd only take it if you're really interested in learning about Bayesian Networks, as it is difficult and a decent amount of work
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