Junction Tree Algorithm for Exact Inference
The Junction Tree Algorithm (JTA) is a popular, but quite sophisticated, algorithm used for exact inference in Bayesian Belief Network. Here are the conceptual steps visualized and explained.
Probabilistic Inference in Gaussian Networks
Here’s a short post on probabilistic inference in Gaussian Bayesian Belief Networks. The math is elegant!
The Basics of Causal Inference
Let’s learn the basics of causal inference with Bayesian belief networks (BBNs) using Dr. Judea Pearl’s probability calculus. In particular, let’s see how the do-operator and backdoor criterion may help us estimate causal impact!
Causal Analysis
Go beyond prediction and explanation, and use causal analysis and counterfactuals to discover cause and effect relationships and estimate causal impacts.
Continuing Success with Summer Coding Camps 2020
Dear Parents, We hope this message finds you, your family and loved ones, well and safe. We are excited and please to announce that One-Off Coder will be re-opening our physical facility on June 8, 2020. Our 10-weeks of engaging, educational and fun Summer Coding Camps will start on June […]