Learner Reviews & Feedback for Probabilistic Graphical Models 2: Inference by Stanford University

It's absolutely very very hard but extremely interesting course! Although code assignments always have a lot of small bugs, and it cost me lots of time to find out, but, hey! Everything is the same in school(offline), nothing gonna be perfect. The sampling part is the most difficult stuff to learn so far, and after I tried to review it again and again, combined with other online material, I got those shit done! The only drawback of this course is that not many people active in the forum(Including those TA), maybe that just because only a small number of people enrolled in this course. In short, worth learning!

great course, though really advanced. would like a bit more examples especially regarding the coding. worth it overally

Great introduction to inference. Requires some extra reading from the textbook.

Pretty good course, albeit very dense compared to the first one (which was certainly not trivial). I would give it 5 stars just based on the content, but the programming assignments don't work without significant extra effort. I completed the honors track for the first course, but gave up after spending 4 hours trying to fix HW bugs that were reported 8 months ago.

Would have also been nice to have more practical examples to work on. Some of the material is very theoretical, and I find it hard to build intuitions without applying the algorithms in practice.

hope to get some feedbacks about hw or exam

Good course, but the material really needs a refresh!

not very clear from the top-down level.

Very great course! A lot of things have been learnt. The lectures, quiz and assignments clear up all key concepts. Especially, assignments are wonderful!

This is a great course

Excellent!

Great course! Expect to spend significant time reviewing the material.

Awesome class!

awesome

Very interesting course. However, even after completing it with honors, I feel like I don't understand a lot.

Difficult, but it makes you think a lot!

Interest but difficult.

I would have like to complete the honors assignments, unfortunately, I'm not fluent in Matlab. Otherwise, great course!

Very interesting, more advanced material

Perhaps the best introduction to AI/ML - especially for those who think "the future ain't what it used to be"; the mathematical techniques covered by the course form a toolkit which can be easily thought of as "core", i.e. a locus of strength which enables a wide universe of thinking about complex problems (many of which were correctly not thought to be tractable in practice until very recently!)...

Thank You for all.

good way to learn PGM,

Really a interesting, challenging and great course!

Had a wonderful and enriching fun filled experience, Thank you Daphne Ma'am

I kind of like the teacher. She can always explain complicated things in a simple way, though the notes she writes in the slides are all in free style. Loopy belief propagation and dual decomposition are the best things I've learnt in this course. I've met them before in some papers, but I found it extremely hard to understand then. Now I gain some significant intuition of them and I'm ready to do further exploration. Anyway, I'll keep on learning course 3 to achieve my first little goal in courser.

Great job Prof. Koller!