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

Daphne Koller

Instructor: Daphne Koller

28,407 already enrolled

Get in-depth knowledge of a subject
4.6

(1,280 reviews)

Advanced level
Designed for those already in the industry
4 months
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
4.6

(1,280 reviews)

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

Details to know

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Taught in English

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Specialization - 3 course series

Probabilistic Graphical Models 1: Representation

Course 166 hours4.6 (1,433 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 (485 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 (299 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 Courses95,655 learners

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