Stanford University
Probabilistic Graphical Models Specialization
Stanford University

Probabilistic Graphical Models Specialization

Probabilistic Graphical Models. Master a new way of reasoning and learning in complex domains

Taught in English

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Daphne Koller

Instructor: Daphne Koller

25,804 already enrolled

Specialization - 3 course series

Get in-depth knowledge of a subject

4.6

(1,273 reviews)

Advanced level
Designed for those already in the industry
4 months at 10 hours a week
Flexible schedule
Learn at your own pace

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Specialization - 3 course series

Get in-depth knowledge of a subject

4.6

(1,273 reviews)

Advanced level
Designed for those already in the industry
4 months at 10 hours a week
Flexible schedule
Learn at your own pace

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Specialization - 3 course series

Probabilistic Graphical Models 1: Representation

Course 166 hours4.6 (1,428 ratings)

What you'll learn

Skills you'll gain

Category: Bayesian Network
Category: Graphical Model
Category: Markov Random Field

Probabilistic Graphical Models 2: Inference

Course 238 hours4.6 (483 ratings)

What you'll learn

Skills you'll gain

Category: Inference
Category: Gibbs Sampling
Category: Markov Chain Monte Carlo (MCMC)
Category: Belief Propagation

Probabilistic Graphical Models 3: Learning

Course 366 hours4.6 (298 ratings)

What you'll learn

Skills you'll gain

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

Instructor

Daphne Koller
Stanford University
3 Courses94,331 learners

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