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Probabilistic Graphical Models

In this class, you will learn the basics of the PGM representation and how to construct them, using both human knowledge and machine learning techniques.

Start Date: Apr 01, 2013 Topics: Machine Learning

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Overview

Description

This graduate-level course covers the essentials of probabilistic graphical models and their applications: the representation of Bayesian and Markov networks; exact and approximate inference in these networks; and parameter and structure learning.

Details

  • Dates: Apr 01, 2013 to Apr 01, 2013
  • Level of Difficulty: Beginner
  • Size: Massive Open Online Course
  • Instructor: Daphne Koller
  • Institution: Coursera
  • Topics: Machine Learning

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About Coursera: Coursera is an education company that partners with the top universities and organizations in the world to offer courses online for anyone to take, for free.

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