10-601 GM1
From Cohen Courses
This a lecture used in the Syllabus for Machine Learning 10-601 in Fall 2014
Slides
Readings
- Chapter 6.11 Mitchell
- Chapter 10 Murphy
- Or: Chap 8.1 and 8.2.2 (Bishop)
Taking home message
- factorization theorem of BN
- Full, independent and intermediate conditional probability models
- Markov blanket
- Learning a BN
- Inference in BN is NP hard
- Approximate inference in BN