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Probabilistic Graphical Models 1: Representation に戻る

スタンフォード大学(Stanford University) による Probabilistic Graphical Models 1: Representation の受講者のレビューおよびフィードバック

4.6
1,375件の評価
306件のレビュー

コースについて

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....

人気のレビュー

ST

2017年7月12日

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

2017年10月22日

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).

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Probabilistic Graphical Models 1: Representation: 176 - 200 / 299 レビュー

by Frédéric L M

2017年11月19日

Great course !

by Diego T

2017年6月9日

Great content!

by Yue S

2019年5月9日

Great course!

by David D

2017年5月30日

Mind blowing!

by Yang P

2017年4月26日

Great course.

by Nairouz M

2017年2月13日

Very helpful.

by brotherzhao

2020年2月15日

nice course!

by Utkarsh A

2018年12月30日

maza aa gaya

by Musalula S

2018年8月2日

Great course

by Yuri F

2017年5月15日

great course

by 赵紫川

2016年11月27日

Nice course.

by Pedro R

2016年11月9日

great course

by Frank

2017年12月14日

老师太天马行空了。。。

by HOLLY W

2019年5月24日

课程特别好,资料丰富

by Siyeong L

2017年1月21日

Awesome!!!

by Alireza N

2017年1月12日

Excellent!

by dingjingtao

2017年1月7日

excellent!

by Phan T B

2016年12月2日

very good!

by Jax

2017年1月8日

very nice

by Jose A A S

2016年11月25日

Wonderful

by mohammed o

2016年10月18日

Fantastic

by zhou

2016年10月13日

very good

by 张浩悦

2018年11月22日

funny!!

by Alexander A S G

2017年2月9日

Thanks

by oilover

2016年12月2日

老师很棒!!