Inference in Temporal Models

Loading...
View Syllabus

Skills You'll Learn

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

Reviews

4.6 (354 ratings)
  • 5 stars
    243 ratings
  • 4 stars
    82 ratings
  • 3 stars
    20 ratings
  • 2 stars
    3 ratings
  • 1 star
    6 ratings
JL

Apr 09, 2018

I would have like to complete the honors assignments, unfortunately, I'm not fluent in Matlab. Otherwise, great course!

EZ

Mar 10, 2018

Very interesting course. However, even after completing it with honors, I feel like I don't understand a lot.

From the lesson
Inference in Temporal Models
In this brief lesson, we discuss some of the complexities of applying some of the exact or approximate inference algorithms that we learned earlier in this course to dynamic Bayesian networks.

Taught By

  • Daphne Koller

    Daphne Koller

    Professor

Explore our Catalog

Join for free and get personalized recommendations, updates and offers.