Chevron Left
Back to Probabilistic Graphical Models 1: Representation

Learner Reviews & Feedback for Probabilistic Graphical Models 1: Representation by Stanford University

4.6
stars
1,401 ratings

About the Course

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more. They are the basis for the state-of-the-art methods in a wide variety of applications, such as medical diagnosis, image understanding, speech recognition, natural language processing, and many, many more. They are also a foundational tool in formulating many machine learning problems. This course is the first in a sequence of three. It describes the two basic PGM representations: Bayesian Networks, which rely on a directed graph; and Markov networks, which use an undirected graph. The course discusses both the theoretical properties of these representations as well as their use in practice. The (highly recommended) honors track contains several hands-on assignments on how to represent some real-world problems. The course also presents some important extensions beyond the basic PGM representation, which allow more complex models to be encoded compactly....

Top reviews

ST

Jul 12, 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 22, 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).

Filter by:

226 - 250 of 304 Reviews for Probabilistic Graphical Models 1: Representation

By Hanbo L

Apr 29, 2017

By Rick

Apr 20, 2017

By 邓成标

Nov 30, 2017

By Surender K

Nov 7, 2016

By Akshaya T

Jan 16, 2018

By Rajeev B A

Dec 23, 2017

By Alain M

Nov 3, 2018

By Boxiao M

Jun 28, 2017

By Yiting T

Oct 15, 2022

By Shawn C

Nov 5, 2016

By Shane C

May 18, 2020

By Hilmi E

Feb 16, 2020

By Nimo F B

Sep 10, 2020

By Roman S

Mar 20, 2018

By Serge S

Oct 18, 2016

By Jack A

Nov 5, 2017

By Francois L

Mar 16, 2020

By Gorazd H R

Jul 7, 2018

By Ashwin P

Jan 9, 2017

By Forest R

Feb 20, 2018

By Иван М

Apr 26, 2020

By Victor Z

Dec 22, 2018

By Luiz C

Jun 26, 2018

By Saurabh N

Mar 24, 2020

By Werner N

Dec 28, 2016