PGM Course Summary

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Просмотреть программу курса

Получаемые навыки

Algorithms, Expectation–Maximization (EM) Algorithm, Graphical Model, Markov Random Field

Рецензии

4.6 (оценок: 294)

  • 5 stars
    71,42 %
  • 4 stars
    19,72 %
  • 3 stars
    5,44 %
  • 2 stars
    2,72 %
  • 1 star
    0,68 %

ZZ

13 февр. 2017 г.

Great course! Very informative course videos and challenging yet rewarding programming assignments. Hope that the mentors can be more helpful in timely responding for questions.

MV

29 апр. 2020 г.

Great course, especially the programming assignments. Textbook is pretty much necessary for some quizzes, definitely for the final one.

Из урока

PGM Wrapup

This module contains an overview of PGM methods as a whole, discussing some of the real-world tradeoffs when using this framework in practice. It refers to topics from all three of the PGM courses.

Преподаватели

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    Daphne Koller

    Professor

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