#1033 overall
Probabilistic Graphical Models Specialization
Coursera
1 recommender · 1 thread · recommended in 1 year, 2018 · score 0.7
A Coursera specialization by Daphne Koller's Stanford-affiliated team covering probabilistic graphical models: representing uncertainty with Bayesian and Markov networks, inference, and learning these models from data.
One commenter recommends it as a MOOC for getting into graphical models and probabilistic programming, which they describe as a growing AI trend.
Machine Learning & AIadvancedinteractive MOOC#probabilistic graphical models#bayesian networks#markov networks#inference#koller
Recommendations by year
20062026
Graphical models[0] & probabilistic programming[1], with the latter making it easier for developers to dive into this growing AI trend. Research in the field for the past decade has been steadily booming with more companies like Microsoft leading the way. I recommend checking out some MOOCs[2] in coursera.
[0]http://www.computervisionblog.com/2015/04/deep-learning-vs-p...
[1]http://probabilistic-programming.org/wiki/Home
[2]https://www.coursera.org/specializations/probabilistic-graph...