Avis et commentaires pour d'étudiants pour Probabilistic Graphical Models 1: Representation par Université de Stanford
À propos du cours
Meilleurs avis
ST
Jul 13, 2017
Prof. Koller did a great job communicating difficult material in an accessible manner. Thanks to her for starting Coursera and offering this advanced course so that we can all learn...Kudos!!
CM
Oct 23, 2017
The course was deep, and well-taught. This is not a spoon-feeding course like some others. The only downside were some "mechanical" problems (e.g. code submission didn't work for me).
226 - 250 sur 275 Avis pour Probabilistic Graphical Models 1: Representation
par Luiz C
•Jun 26, 2018
Good course, quite complex, wish some better quality slides, and more quizzes to help understand the theory
par Saurabh N
•Mar 24, 2020
The coding assignments can be compulsory too.
Maybe not as vast, but maybe interleaved with the quizzes
par Werner N
•Dec 28, 2016
Very good course. It should contain more practical examples to make the material better to understand.
par Haitham S
•Nov 24, 2016
Great course, however, the honors track assignments are a bit too tedious and take lots of time.
par Kevin W
•Jan 17, 2017
The course is pretty good. I love the way that the professor led us into the graphical models.
par Péter D
•Oct 29, 2017
great job, although the last PA is a huge pain / difficulty spike - more hints would be nice
par Andres P N
•Jun 27, 2018
There are many error in the implementations for octave. Aside from that, the course is fine
par Ahmad E
•Aug 20, 2017
Covers some material a little too quickly, but overall a good and entertaining course.
par Soteris S
•Nov 27, 2017
A bit more challenging than I thought but very useful, and very well structured
par mathieu.zaradzki@gmail.com
•Oct 04, 2016
Great and well paced content.
Quizzes really helps nailing the tricky points.
par Caio A M M
•Dec 03, 2016
Instructor is engaging in her delivery. Topic is interesting but difficult.
par Michael B
•Dec 12, 2019
Honors seems like a must to full instill concepts/implementation
par Anshuman S
•May 08, 2019
I would recommend adding some supplemental reading material.
par Jhonatan d S O
•May 25, 2017
Rich content and useful tools for applying in real problems
par Vahan A
•May 31, 2020
Please, provide programming assignments on Python or C++
par Alberto C
•Dec 01, 2017
Theory: Very interesting. Assignments: not so useful.
par Yuanduo H
•Jan 20, 2020
Five stars minus the week 4 coding homework
par Arthur B
•Jan 08, 2017
More feedback from TA would be appreciated
par Myoungsu C
•Dec 26, 2018
Writing on the ppt is not clear to see.
par Soumyadipta D
•Jul 16, 2019
lectures are too fast otherwise great
par Sunsik K
•Jul 31, 2018
Broad introduction to general issues
par Tianyi X
•Feb 20, 2018
Lack of top-down review of the PGM.
par Sunil
•Sep 12, 2017
Great intro to probabilistic models
par Nikesh B
•Nov 06, 2016
Excellent
par Tianqi Y
•Jun 20, 2019
too hard
